library(tidyr)
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(ggplot2)
library(plyr)
## -------------------------------------------------------------------------
## You have loaded plyr after dplyr - this is likely to cause problems.
## If you need functions from both plyr and dplyr, please load plyr first, then dplyr:
## library(plyr); library(dplyr)
## -------------------------------------------------------------------------
##
## Attaching package: 'plyr'
## The following objects are masked from 'package:dplyr':
##
## arrange, count, desc, failwith, id, mutate, rename, summarise,
## summarize
library(stringr)
library(DataExplorer)
library(cbanalysis)
library(gvlma)
library(stargazer)
##
## Please cite as:
## Hlavac, Marek (2018). stargazer: Well-Formatted Regression and Summary Statistics Tables.
## R package version 5.2.2. https://CRAN.R-project.org/package=stargazer
library(knitr)
crime <- read.csv("https://raw.githubusercontent.com/xkong100/data-621/master/HW%203/crime-training-data.csv", stringsAsFactors = FALSE, check.names = FALSE, na.strings = c("", "NA"))
head(crime)
## zn indus chas nox rm age dis rad tax ptratio black lstat medv
## 1 0 19.58 0 0.605 7.929 96.2 2.0459 5 403 14.7 369.30 3.70 50.0
## 2 0 19.58 1 0.871 5.403 100.0 1.3216 5 403 14.7 396.90 26.82 13.4
## 3 0 18.10 0 0.740 6.485 100.0 1.9784 24 666 20.2 386.73 18.85 15.4
## 4 30 4.93 0 0.428 6.393 7.8 7.0355 6 300 16.6 374.71 5.19 23.7
## 5 0 2.46 0 0.488 7.155 92.2 2.7006 3 193 17.8 394.12 4.82 37.9
## 6 0 8.56 0 0.520 6.781 71.3 2.8561 5 384 20.9 395.58 7.67 26.5
## target
## 1 1
## 2 1
## 3 1
## 4 0
## 5 0
## 6 0
nrow(crime)
## [1] 466
ncol(crime)
## [1] 14
plot_missing(crime)

summary(crime)
## zn indus chas nox
## Min. : 0.00 Min. : 0.460 Min. :0.00000 Min. :0.3890
## 1st Qu.: 0.00 1st Qu.: 5.145 1st Qu.:0.00000 1st Qu.:0.4480
## Median : 0.00 Median : 9.690 Median :0.00000 Median :0.5380
## Mean : 11.58 Mean :11.105 Mean :0.07082 Mean :0.5543
## 3rd Qu.: 16.25 3rd Qu.:18.100 3rd Qu.:0.00000 3rd Qu.:0.6240
## Max. :100.00 Max. :27.740 Max. :1.00000 Max. :0.8710
## rm age dis rad
## Min. :3.863 Min. : 2.90 Min. : 1.130 Min. : 1.00
## 1st Qu.:5.887 1st Qu.: 43.88 1st Qu.: 2.101 1st Qu.: 4.00
## Median :6.210 Median : 77.15 Median : 3.191 Median : 5.00
## Mean :6.291 Mean : 68.37 Mean : 3.796 Mean : 9.53
## 3rd Qu.:6.630 3rd Qu.: 94.10 3rd Qu.: 5.215 3rd Qu.:24.00
## Max. :8.780 Max. :100.00 Max. :12.127 Max. :24.00
## tax ptratio black lstat
## Min. :187.0 Min. :12.6 Min. : 0.32 Min. : 1.730
## 1st Qu.:281.0 1st Qu.:16.9 1st Qu.:375.61 1st Qu.: 7.043
## Median :334.5 Median :18.9 Median :391.34 Median :11.350
## Mean :409.5 Mean :18.4 Mean :357.12 Mean :12.631
## 3rd Qu.:666.0 3rd Qu.:20.2 3rd Qu.:396.24 3rd Qu.:16.930
## Max. :711.0 Max. :22.0 Max. :396.90 Max. :37.970
## medv target
## Min. : 5.00 Min. :0.0000
## 1st Qu.:17.02 1st Qu.:0.0000
## Median :21.20 Median :0.0000
## Mean :22.59 Mean :0.4914
## 3rd Qu.:25.00 3rd Qu.:1.0000
## Max. :50.00 Max. :1.0000
s<- stargazer(crime,type="text", title="Results", align=TRUE)
##
## Results
## ===============================================================
## Statistic N Mean St. Dev. Min Pctl(25) Pctl(75) Max
## ---------------------------------------------------------------
## zn 466 11.577 23.365 0 0 16.2 100
## indus 466 11.105 6.846 0.460 5.145 18.100 27.740
## chas 466 0.071 0.257 0 0 0 1
## nox 466 0.554 0.117 0.389 0.448 0.624 0.871
## rm 466 6.291 0.705 3.863 5.887 6.630 8.780
## age 466 68.368 28.321 2.900 43.875 94.100 100.000
## dis 466 3.796 2.107 1.130 2.101 5.215 12.127
## rad 466 9.530 8.686 1 4 24 24
## tax 466 409.502 167.900 187 281 666 711
## ptratio 466 18.398 2.197 12.600 16.900 20.200 22.000
## black 466 357.120 91.321 0.320 375.607 396.238 396.900
## lstat 466 12.631 7.102 1.730 7.043 16.930 37.970
## medv 466 22.589 9.240 5 17.0 25 50
## target 466 0.491 0.500 0 0 1 1
## ---------------------------------------------------------------
plot_histogram(crime)

cor(crime)
## zn indus chas nox rm
## zn 1.00000000 -0.53826643 -0.04016203 -0.51704518 0.31981410
## indus -0.53826643 1.00000000 0.06118317 0.75963008 -0.39271181
## chas -0.04016203 0.06118317 1.00000000 0.09745577 0.09050979
## nox -0.51704518 0.75963008 0.09745577 1.00000000 -0.29548972
## rm 0.31981410 -0.39271181 0.09050979 -0.29548972 1.00000000
## age -0.57258054 0.63958182 0.07888366 0.73512782 -0.23281251
## dis 0.66012434 -0.70361886 -0.09657711 -0.76888404 0.19901584
## rad -0.31548119 0.60062839 -0.01590037 0.59582984 -0.20844570
## tax -0.31928408 0.73222922 -0.04676476 0.65387804 -0.29693430
## ptratio -0.39103573 0.39468980 -0.12866058 0.17626871 -0.36034706
## black 0.17941504 -0.35813561 0.04444450 -0.38015487 0.13266756
## lstat -0.43299252 0.60711023 -0.05142322 0.59624264 -0.63202445
## medv 0.37671713 -0.49617432 0.16156528 -0.43012267 0.70533679
## target -0.43168176 0.60485074 0.08004187 0.72610622 -0.15255334
## age dis rad tax ptratio
## zn -0.57258054 0.66012434 -0.31548119 -0.31928408 -0.3910357
## indus 0.63958182 -0.70361886 0.60062839 0.73222922 0.3946898
## chas 0.07888366 -0.09657711 -0.01590037 -0.04676476 -0.1286606
## nox 0.73512782 -0.76888404 0.59582984 0.65387804 0.1762687
## rm -0.23281251 0.19901584 -0.20844570 -0.29693430 -0.3603471
## age 1.00000000 -0.75089759 0.46031430 0.51212452 0.2554479
## dis -0.75089759 1.00000000 -0.49499193 -0.53425464 -0.2333394
## rad 0.46031430 -0.49499193 1.00000000 0.90646323 0.4714516
## tax 0.51212452 -0.53425464 0.90646323 1.00000000 0.4744223
## ptratio 0.25544785 -0.23333940 0.47145160 0.47442229 1.0000000
## black -0.27346774 0.29384407 -0.44637503 -0.44250586 -0.1816395
## lstat 0.60562001 -0.50752800 0.50310125 0.56418864 0.3773560
## medv -0.37815605 0.25669476 -0.39766826 -0.49003287 -0.5159153
## target 0.63010625 -0.61867312 0.62810492 0.61111331 0.2508489
## black lstat medv target
## zn 0.1794150 -0.43299252 0.3767171 -0.43168176
## indus -0.3581356 0.60711023 -0.4961743 0.60485074
## chas 0.0444445 -0.05142322 0.1615653 0.08004187
## nox -0.3801549 0.59624264 -0.4301227 0.72610622
## rm 0.1326676 -0.63202445 0.7053368 -0.15255334
## age -0.2734677 0.60562001 -0.3781560 0.63010625
## dis 0.2938441 -0.50752800 0.2566948 -0.61867312
## rad -0.4463750 0.50310125 -0.3976683 0.62810492
## tax -0.4425059 0.56418864 -0.4900329 0.61111331
## ptratio -0.1816395 0.37735605 -0.5159153 0.25084892
## black 1.0000000 -0.35336588 0.3300286 -0.35295680
## lstat -0.3533659 1.00000000 -0.7358008 0.46912702
## medv 0.3300286 -0.73580078 1.0000000 -0.27055071
## target -0.3529568 0.46912702 -0.2705507 1.00000000
pairs(crime)

library(moments)
skewness(crime)
## zn indus chas nox rm age
## 2.18384094 0.28947632 3.34625531 0.74873687 0.48086725 -0.57957212
## dis rad tax ptratio black lstat
## 1.00211659 1.01353947 0.66144159 -0.75670251 -2.92572328 0.90850923
## medv target
## 1.08016704 0.03433982
d1 <- density(crime$target)
plot(d1, main="Density of the median crime rate")
polygon(d1,col="red")

d2 <- density(crime$indus)
plot(d2, main="Density of the non-retail business")
polygon(d2,col="blue")

d3 <- density(crime$nox)
plot(d3, main="Density of nitrogen oxides concentration")
polygon(d3,col="yellow")

d4 <- density(crime$age)
plot(d4, main="Density of proportion of owner-occupied units prior to 1940")
polygon(d4,col="pink")

d5 <- density(crime$dis)
plot(d5, main="Density of the weighted mean of distance to employment center")
polygon(d5,col="green")

d6 <- density(crime$tax)
plot(d6, main="Density of full-value property tax rate")
polygon(d6,col="purple")

boxplot(crime$indus,col="blue")

boxplot(crime$nox, col="yellow")

boxplot(crime$age, col="pink")

boxplot(crime$dis, col="green")

boxplot(crime$tax, col="purple")

library(rcompanion)
# age
plotNormalHistogram(crime$age, main="age")

qqnorm(crime$age, ylab="age")
qqline(crime$age,col="red")

T_sqrt_age <- sqrt(101-crime$age)
plotNormalHistogram(T_sqrt_age)

qqnorm(T_sqrt_age)
qqline(T_sqrt_age, col="red")

skewness(T_sqrt_age)
## [1] 0.07195121
T_cubic_age <- (101-crime$age)^(1/3)
plotNormalHistogram(T_cubic_age)

qqnorm(T_cubic_age)
qqline(T_cubic_age, col="blue")

skewness(T_cubic_age)
## [1] -0.1518753
T_log_age <- log(101-crime$age)
plotNormalHistogram(T_log_age)

qqnorm(T_log_age)
qqline(T_log_age,col="green")

skewness(T_log_age)
## [1] -0.7097797
# ptratio
plotNormalHistogram(crime$ptratio, main="ptratio")

qqnorm(crime$ptratio, ylab="ptratio")
qqline(crime$ptratio,col="red")

T_sqrt_ptratio <- sqrt(23-crime$ptratio)
plotNormalHistogram(T_sqrt_ptratio)

qqnorm(T_sqrt_ptratio)
qqline(T_sqrt_ptratio, col="red")

skewness(T_sqrt_ptratio)
## [1] 0.4156387
T_cubic_ptratio <- (23-crime$ptratio)^(1/3)
plotNormalHistogram(T_cubic_ptratio)

qqnorm(T_cubic_ptratio)
qqline(T_cubic_ptratio, col="blue")

skewness(T_cubic_ptratio)
## [1] 0.2952715
T_log_ptratio <- log(23-crime$ptratio)
plotNormalHistogram(T_log_ptratio)

qqnorm(T_log_ptratio)
qqline(T_log_ptratio,col="green")

skewness(T_log_ptratio)
## [1] 0.03604803
# dis
plotNormalHistogram(crime$dis, main="dis")

qqnorm(crime$dis, ylab="dis")
qqline(crime$dis,col="red")

T_sqrt_dis <- sqrt(crime$dis)
plotNormalHistogram(T_sqrt_dis)

qqnorm(T_sqrt_dis)
qqline(T_sqrt_dis, col="red")

skewness(T_sqrt_dis)
## [1] 0.5524993
T_cubic_dis <- (crime$dis)^(1/3)
plotNormalHistogram(T_cubic_dis)

qqnorm(T_cubic_dis)
qqline(T_cubic_dis, col="blue")

skewness(T_cubic_dis)
## [1] 0.4127918
T_log_dis <- log(crime$dis)
plotNormalHistogram(T_log_dis)

qqnorm(T_log_dis)
qqline(T_log_dis,col="green")

skewness(T_log_dis)
## [1] 0.1431555
#lstat
plotNormalHistogram(crime$lstat, main="lstat")

qqnorm(crime$lstat, ylab="lstat")
qqline(crime$lstat,col="red")

T_sqrt_lstat <- sqrt(crime$lstat)
plotNormalHistogram(T_sqrt_lstat)

qqnorm(T_sqrt_lstat)
qqline(T_sqrt_lstat, col="red")

skewness(T_sqrt_lstat)
## [1] 0.3042474
T_cubic_lstat <- (crime$lstat)^(1/3)
plotNormalHistogram(T_cubic_lstat)

qqnorm(T_cubic_lstat)
qqline(T_cubic_lstat, col="blue")

skewness(T_cubic_lstat)
## [1] 0.09875891
T_log_lstat <- log(crime$lstat)
plotNormalHistogram(T_log_lstat)

qqnorm(T_log_lstat)
qqline(T_log_lstat,col="green")

skewness(T_log_lstat)
## [1] -0.3291453
attach(crime)
trans_crime <- crime %>% mutate(sage=T_sqrt_age,lptratio=T_log_ptratio,ldis= T_log_dis, clstat=T_cubic_lstat) %>% dplyr ::select(-age,-ptratio,-dis,-lstat)
head(trans_crime)
## zn indus chas nox rm rad tax black medv target sage lptratio
## 1 0 19.58 0 0.605 7.929 5 403 369.30 50.0 1 2.190890 2.1162555
## 2 0 19.58 1 0.871 5.403 5 403 396.90 13.4 1 1.000000 2.1162555
## 3 0 18.10 0 0.740 6.485 24 666 386.73 15.4 1 1.000000 1.0296194
## 4 30 4.93 0 0.428 6.393 6 300 374.71 23.7 0 9.654015 1.8562980
## 5 0 2.46 0 0.488 7.155 3 193 394.12 37.9 0 2.966479 1.6486586
## 6 0 8.56 0 0.520 6.781 5 384 395.58 26.5 0 5.449771 0.7419373
## ldis clstat
## 1 0.7158378 1.546680
## 2 0.2788431 2.993318
## 3 0.6822884 2.661361
## 4 1.9509688 1.731367
## 5 0.9934740 1.689205
## 6 1.0494571 1.972113
m1 <-glm(target~., family= "binomial", data=crime)
plot(m1)




summary(m1)
##
## Call:
## glm(formula = target ~ ., family = "binomial", data = crime)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.2854 -0.1372 -0.0017 0.0020 3.4721
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -36.839521 7.028726 -5.241 1.59e-07 ***
## zn -0.061720 0.034410 -1.794 0.072868 .
## indus -0.072580 0.048546 -1.495 0.134894
## chas 1.032352 0.759627 1.359 0.174139
## nox 50.159513 8.049503 6.231 4.62e-10 ***
## rm -0.692145 0.741431 -0.934 0.350548
## age 0.034522 0.013883 2.487 0.012895 *
## dis 0.765795 0.234407 3.267 0.001087 **
## rad 0.663015 0.165135 4.015 5.94e-05 ***
## tax -0.006593 0.003064 -2.152 0.031422 *
## ptratio 0.442217 0.132234 3.344 0.000825 ***
## black -0.013094 0.006680 -1.960 0.049974 *
## lstat 0.047571 0.054508 0.873 0.382802
## medv 0.199734 0.071022 2.812 0.004919 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 645.88 on 465 degrees of freedom
## Residual deviance: 186.15 on 452 degrees of freedom
## AIC: 214.15
##
## Number of Fisher Scoring iterations: 9
m2 <- glm(target~indus+nox+age+dis+tax+ptratio+medv+lstat, family="binomial", data=crime)
plot(m2)




summary(m2)
##
## Call:
## glm(formula = target ~ indus + nox + age + dis + tax + ptratio +
## medv + lstat, family = "binomial", data = crime)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.1439 -0.3840 -0.0610 0.1931 2.8119
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -36.267175 5.074854 -7.146 8.91e-13 ***
## indus -0.116645 0.044554 -2.618 0.008844 **
## nox 41.770158 6.477664 6.448 1.13e-10 ***
## age 0.022585 0.009984 2.262 0.023691 *
## dis 0.444086 0.152570 2.911 0.003606 **
## tax 0.004582 0.001598 2.866 0.004151 **
## ptratio 0.320116 0.093793 3.413 0.000643 ***
## medv 0.147921 0.034328 4.309 1.64e-05 ***
## lstat 0.057610 0.043329 1.330 0.183654
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 645.88 on 465 degrees of freedom
## Residual deviance: 251.13 on 457 degrees of freedom
## AIC: 269.13
##
## Number of Fisher Scoring iterations: 7
#transform
m3 <-glm(target~., family= "binomial", data=trans_crime)
plot(m3)




summary(m3)
##
## Call:
## glm(formula = target ~ ., family = "binomial", data = trans_crime)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.9953 -0.1091 -0.0020 0.0015 3.5152
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -20.823841 7.519484 -2.769 0.005617 **
## zn -0.056953 0.031518 -1.807 0.070767 .
## indus -0.026405 0.051044 -0.517 0.604953
## chas 0.895290 0.761867 1.175 0.239944
## nox 48.726617 7.683147 6.342 2.27e-10 ***
## rm -1.215808 0.773727 -1.571 0.116098
## rad 0.745502 0.177083 4.210 2.55e-05 ***
## tax -0.006114 0.003247 -1.883 0.059729 .
## black -0.010808 0.006162 -1.754 0.079469 .
## medv 0.240441 0.073483 3.272 0.001068 **
## sage -0.465443 0.143417 -3.245 0.001173 **
## lptratio -2.137684 0.552340 -3.870 0.000109 ***
## ldis 3.660742 0.967109 3.785 0.000154 ***
## clstat 0.011269 0.998199 0.011 0.990992
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 645.88 on 465 degrees of freedom
## Residual deviance: 175.22 on 452 degrees of freedom
## AIC: 203.22
##
## Number of Fisher Scoring iterations: 9
m4 <- glm(target~indus+nox+sage+ldis+tax+lptratio+medv+clstat, family="binomial", data=trans_crime)
plot(m4)




summary(m4)
##
## Call:
## glm(formula = target ~ indus + nox + sage + ldis + tax + lptratio +
## medv + clstat, family = "binomial", data = trans_crime)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.17783 -0.36004 -0.06073 0.16792 2.89893
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -31.142224 4.983598 -6.249 4.13e-10 ***
## indus -0.101450 0.047486 -2.136 0.032646 *
## nox 45.375324 6.615202 6.859 6.92e-12 ***
## sage -0.297497 0.106595 -2.791 0.005256 **
## ldis 2.840540 0.723185 3.928 8.57e-05 ***
## tax 0.005386 0.001686 3.196 0.001395 **
## lptratio -1.387024 0.396106 -3.502 0.000462 ***
## medv 0.167663 0.038331 4.374 1.22e-05 ***
## clstat 0.841858 0.754336 1.116 0.264411
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 645.88 on 465 degrees of freedom
## Residual deviance: 241.25 on 457 degrees of freedom
## AIC: 259.25
##
## Number of Fisher Scoring iterations: 7
# Select models
library(lmtest)
## Loading required package: zoo
##
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric
lrtest(m1, m2, m3, m4)
## Likelihood ratio test
##
## Model 1: target ~ zn + indus + chas + nox + rm + age + dis + rad + tax +
## ptratio + black + lstat + medv
## Model 2: target ~ indus + nox + age + dis + tax + ptratio + medv + lstat
## Model 3: target ~ zn + indus + chas + nox + rm + rad + tax + black + medv +
## sage + lptratio + ldis + clstat
## Model 4: target ~ indus + nox + sage + ldis + tax + lptratio + medv +
## clstat
## #Df LogLik Df Chisq Pr(>Chisq)
## 1 14 -93.074
## 2 9 -125.564 -5 64.981 1.131e-12 ***
## 3 14 -87.608 5 75.912 6.002e-15 ***
## 4 9 -120.627 -5 66.037 6.827e-13 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
library(pscl)
## Classes and Methods for R developed in the
## Political Science Computational Laboratory
## Department of Political Science
## Stanford University
## Simon Jackman
## hurdle and zeroinfl functions by Achim Zeileis
pR2(m1)
## llh llhNull G2 McFadden r2ML
## -93.0736803 -322.9379132 459.7284658 0.7117908 0.6271361
## r2CU
## 0.8362636
pR2(m2)
## llh llhNull G2 McFadden r2ML
## -125.5642433 -322.9379132 394.7473398 0.6111815 0.5713426
## r2CU
## 0.7618650
pR2(m3)
## llh llhNull G2 McFadden r2ML
## -87.6084007 -322.9379132 470.6590251 0.7287144 0.6357803
## r2CU
## 0.8477903
pR2(m4)
## llh llhNull G2 McFadden r2ML
## -120.6270630 -322.9379132 404.6217004 0.6264698 0.5803301
## r2CU
## 0.7738496
test_result1 <- predict(m1, newdata=crime,type='response')
df <- bind_cols(crime, data.frame(scored_target=test_result1))%>% mutate(scored_target=ifelse(scored_target>0.5, 1, 0)) %>% print
## zn indus chas nox rm age dis rad tax ptratio black
## 1 0.0 19.58 0 0.6050 7.929 96.2 2.0459 5 403 14.7 369.30
## 2 0.0 19.58 1 0.8710 5.403 100.0 1.3216 5 403 14.7 396.90
## 3 0.0 18.10 0 0.7400 6.485 100.0 1.9784 24 666 20.2 386.73
## 4 30.0 4.93 0 0.4280 6.393 7.8 7.0355 6 300 16.6 374.71
## 5 0.0 2.46 0 0.4880 7.155 92.2 2.7006 3 193 17.8 394.12
## 6 0.0 8.56 0 0.5200 6.781 71.3 2.8561 5 384 20.9 395.58
## 7 0.0 18.10 0 0.6930 5.453 100.0 1.4896 24 666 20.2 396.90
## 8 0.0 18.10 0 0.6930 4.519 100.0 1.6582 24 666 20.2 88.27
## 9 0.0 5.19 0 0.5150 6.316 38.1 6.4584 5 224 20.2 389.71
## 10 80.0 3.64 0 0.3920 5.876 19.1 9.2203 1 315 16.4 395.18
## 11 22.0 5.86 0 0.4310 6.438 8.9 7.3967 7 330 19.1 377.07
## 12 0.0 12.83 0 0.4370 6.286 45.0 4.5026 5 398 18.7 383.23
## 13 0.0 18.10 0 0.5320 7.061 77.0 3.4106 24 666 20.2 395.28
## 14 22.0 5.86 0 0.4310 8.259 8.4 8.9067 7 330 19.1 396.90
## 15 0.0 2.46 0 0.4880 6.153 68.8 3.2797 3 193 17.8 387.11
## 16 0.0 2.18 0 0.4580 6.430 58.7 6.0622 3 222 18.7 394.12
## 17 100.0 1.32 0 0.4110 6.816 40.5 8.3248 5 256 15.1 392.90
## 18 20.0 3.97 0 0.6470 5.560 62.8 1.9865 5 264 13.0 392.40
## 19 0.0 18.10 0 0.6790 5.896 95.4 1.9096 24 666 20.2 7.68
## 20 0.0 18.10 0 0.6710 6.545 99.1 1.5192 24 666 20.2 396.90
## 21 0.0 3.24 0 0.4600 6.144 32.2 5.8736 4 430 16.9 368.57
## 22 0.0 6.20 1 0.5070 6.726 66.5 3.6519 8 307 17.4 360.20
## 23 0.0 2.89 0 0.4450 7.416 62.5 3.4952 2 276 18.0 396.90
## 24 18.0 2.31 0 0.5380 6.575 65.2 4.0900 1 296 15.3 396.90
## 25 0.0 9.90 0 0.5440 6.382 67.2 3.5325 4 304 18.4 395.21
## 26 60.0 2.93 0 0.4010 6.604 18.8 6.2196 1 265 15.6 376.70
## 27 0.0 5.19 0 0.5150 5.985 45.4 4.8122 5 224 20.2 396.90
## 28 0.0 18.10 0 0.7000 5.390 98.9 1.7281 24 666 20.2 396.90
## 29 25.0 4.86 0 0.4260 6.167 46.7 5.4007 4 281 19.0 390.64
## 30 25.0 5.13 0 0.4530 6.456 67.8 7.2255 8 284 19.7 396.90
## 31 0.0 6.20 0 0.5040 5.981 68.1 3.6715 8 307 17.4 378.35
## 32 0.0 8.56 0 0.5200 6.474 97.1 2.4329 5 384 20.9 395.24
## 33 0.0 2.89 0 0.4450 7.820 36.9 3.4952 2 276 18.0 393.53
## 34 0.0 18.10 0 0.6790 6.380 95.6 1.9682 24 666 20.2 60.72
## 35 0.0 5.19 0 0.5150 6.059 37.3 4.8122 5 224 20.2 396.14
## 36 80.0 4.95 0 0.4110 6.630 23.4 5.1167 4 245 19.2 396.90
## 37 0.0 2.46 0 0.4880 7.831 53.6 3.1992 3 193 17.8 392.63
## 38 0.0 18.10 0 0.6140 6.185 96.7 2.1705 24 666 20.2 379.70
## 39 0.0 4.39 0 0.4420 5.898 52.3 8.0136 3 352 18.8 364.61
## 40 0.0 19.58 0 0.6050 6.402 95.2 2.2625 5 403 14.7 330.04
## 41 0.0 3.24 0 0.4600 5.868 25.8 5.2146 4 430 16.9 382.44
## 42 0.0 18.10 0 0.6710 6.649 93.3 1.3449 24 666 20.2 363.02
## 43 0.0 4.05 0 0.5100 5.859 68.7 2.7019 5 296 16.6 393.23
## 44 80.0 1.91 0 0.4130 5.663 21.9 10.5857 4 334 22.0 382.80
## 45 12.5 7.87 0 0.5240 6.009 82.9 6.2267 5 311 15.2 396.90
## 46 0.0 6.91 0 0.4480 6.030 85.5 5.6894 3 233 17.9 392.74
## 47 0.0 18.10 0 0.5830 6.312 51.9 3.9917 24 666 20.2 388.62
## 48 0.0 9.90 0 0.5440 5.782 71.7 4.0317 4 304 18.4 396.90
## 49 0.0 18.10 0 0.5320 6.229 90.7 3.0993 24 666 20.2 395.33
## 50 0.0 8.14 0 0.5380 6.674 87.3 4.2390 4 307 21.0 380.23
## 51 55.0 2.25 0 0.3890 6.453 31.9 7.3073 1 300 15.3 394.72
## 52 12.5 7.87 0 0.5240 6.004 85.9 6.5921 5 311 15.2 386.71
## 53 0.0 5.96 0 0.4990 5.933 68.2 3.3603 5 279 19.2 396.90
## 54 0.0 1.89 0 0.5180 6.540 59.7 6.2669 1 422 15.9 389.96
## 55 0.0 21.89 0 0.6240 5.693 96.0 1.7883 4 437 21.2 392.11
## 56 0.0 10.59 1 0.4890 5.344 100.0 3.8750 4 277 18.6 396.90
## 57 20.0 3.33 0 0.4429 7.820 64.5 4.6947 5 216 14.9 387.31
## 58 20.0 3.33 1 0.4429 7.645 49.7 5.2119 5 216 14.9 377.07
## 59 0.0 7.07 0 0.4690 6.421 78.9 4.9671 2 242 17.8 396.90
## 60 0.0 18.10 0 0.7000 5.000 89.5 1.5184 24 666 20.2 396.90
## 61 0.0 19.58 0 0.6050 5.877 79.2 2.4259 5 403 14.7 227.61
## 62 0.0 9.90 0 0.5440 4.973 37.8 2.5194 4 304 18.4 350.45
## 63 0.0 18.10 0 0.7400 6.459 94.8 1.9879 24 666 20.2 43.06
## 64 45.0 3.44 0 0.4370 6.782 41.1 3.7886 5 398 15.2 393.87
## 65 35.0 6.06 0 0.4379 5.706 28.4 6.6407 1 304 16.9 394.02
## 66 0.0 8.14 0 0.5380 5.949 61.8 4.7075 4 307 21.0 396.90
## 67 0.0 27.74 0 0.6090 5.414 98.3 1.7554 4 711 20.1 344.05
## 68 0.0 18.10 0 0.7180 6.411 100.0 1.8589 24 666 20.2 318.75
## 69 0.0 9.69 0 0.5850 5.390 72.9 2.7986 6 391 19.2 396.90
## 70 0.0 6.20 1 0.5070 6.631 76.5 4.1480 8 307 17.4 388.45
## 71 0.0 18.10 0 0.6310 6.216 100.0 1.1691 24 666 20.2 366.15
## 72 0.0 8.56 0 0.5200 6.167 90.0 2.4210 5 384 20.9 392.69
## 73 0.0 19.58 0 0.6050 5.875 94.6 2.4259 5 403 14.7 292.29
## 74 0.0 13.89 0 0.5500 6.642 85.1 3.4211 5 276 16.4 392.78
## 75 0.0 18.10 0 0.6140 5.304 97.3 2.1007 24 666 20.2 349.48
## 76 0.0 10.81 0 0.4130 6.245 6.2 5.2873 4 305 19.2 377.17
## 77 0.0 19.58 0 0.8710 5.597 94.9 1.5257 5 403 14.7 351.85
## 78 0.0 13.89 1 0.5500 5.888 56.0 3.1121 5 276 16.4 392.80
## 79 0.0 2.18 0 0.4580 6.998 45.8 6.0622 3 222 18.7 394.63
## 80 0.0 7.38 0 0.4930 6.376 54.3 4.5404 5 287 19.6 396.90
## 81 0.0 10.01 0 0.5470 5.913 92.9 2.3534 6 432 17.8 394.95
## 82 0.0 18.10 0 0.5320 6.242 64.7 3.4242 24 666 20.2 396.90
## 83 0.0 18.10 0 0.6930 6.471 98.8 1.7257 24 666 20.2 391.98
## 84 80.0 4.95 0 0.4110 6.861 27.9 5.1167 4 245 19.2 396.90
## 85 20.0 3.97 0 0.5750 8.297 67.0 2.4216 5 264 13.0 384.54
## 86 30.0 4.93 0 0.4280 6.481 18.5 6.1899 6 300 16.6 379.41
## 87 0.0 19.58 0 0.6050 6.943 97.4 1.8773 5 403 14.7 363.43
## 88 0.0 18.10 0 0.6710 6.794 98.8 1.3580 24 666 20.2 396.90
## 89 0.0 10.01 0 0.5470 6.176 72.5 2.7301 6 432 17.8 393.30
## 90 21.0 5.64 0 0.4390 5.963 45.7 6.8147 4 243 16.8 395.56
## 91 25.0 4.86 0 0.4260 6.727 33.5 5.4007 4 281 19.0 396.90
## 92 70.0 2.24 0 0.4000 7.041 10.0 7.8278 5 358 14.8 371.58
## 93 0.0 18.10 0 0.6790 6.782 90.8 1.8195 24 666 20.2 21.57
## 94 0.0 7.38 0 0.4930 6.083 43.7 5.4159 5 287 19.6 396.90
## 95 45.0 3.44 0 0.4370 6.951 21.5 6.4798 5 398 15.2 377.68
## 96 0.0 18.10 0 0.6140 6.229 88.0 1.9512 24 666 20.2 383.32
## 97 40.0 1.25 0 0.4290 6.490 44.4 8.7921 1 335 19.7 396.90
## 98 0.0 18.10 0 0.5970 4.628 100.0 1.5539 24 666 20.2 28.79
## 99 0.0 18.10 0 0.7400 6.461 93.3 2.0026 24 666 20.2 27.49
## 100 0.0 5.19 0 0.5150 6.037 34.5 5.9853 5 224 20.2 396.90
## 101 0.0 8.14 0 0.5380 5.713 94.1 4.2330 4 307 21.0 360.17
## 102 0.0 10.59 0 0.4890 6.326 52.5 4.3549 4 277 18.6 394.87
## 103 0.0 19.58 0 0.8710 5.709 98.5 1.6232 5 403 14.7 261.95
## 104 75.0 4.00 0 0.4100 5.888 47.6 7.3197 3 469 21.1 396.90
## 105 0.0 18.10 0 0.5970 5.155 100.0 1.5894 24 666 20.2 210.97
## 106 0.0 18.10 0 0.7700 6.251 91.1 2.2955 24 666 20.2 350.65
## 107 0.0 11.93 0 0.5730 6.794 89.3 2.3889 1 273 21.0 393.45
## 108 55.0 3.78 0 0.4840 6.874 28.1 6.4654 5 370 17.6 387.97
## 109 0.0 21.89 0 0.6240 6.454 98.4 1.8498 4 437 21.2 394.08
## 110 0.0 3.24 0 0.4600 6.333 17.2 5.2146 4 430 16.9 375.21
## 111 0.0 6.20 0 0.5040 8.725 83.0 2.8944 8 307 17.4 382.00
## 112 25.0 5.13 0 0.4530 6.145 29.2 7.8148 8 284 19.7 390.68
## 113 0.0 5.19 0 0.5150 5.869 46.3 5.2311 5 224 20.2 396.90
## 114 52.5 5.32 0 0.4050 6.209 31.3 7.3172 6 293 16.6 396.90
## 115 0.0 6.91 0 0.4480 5.682 33.8 5.1004 3 233 17.9 396.90
## 116 82.5 2.03 0 0.4150 6.162 38.4 6.2700 2 348 14.7 393.77
## 117 0.0 18.10 0 0.6550 5.952 84.7 2.8715 24 666 20.2 22.01
## 118 0.0 9.90 0 0.5440 5.972 76.7 3.1025 4 304 18.4 396.24
## 119 0.0 21.89 0 0.6240 5.757 98.4 2.3460 4 437 21.2 262.76
## 120 0.0 6.20 0 0.5070 6.618 80.8 3.2721 8 307 17.4 396.90
## 121 0.0 8.14 0 0.5380 5.990 81.7 4.2579 4 307 21.0 386.75
## 122 0.0 6.91 0 0.4480 6.169 6.6 5.7209 3 233 17.9 383.37
## 123 0.0 6.20 0 0.5040 7.412 76.9 3.6715 8 307 17.4 376.14
## 124 0.0 18.10 0 0.6590 5.608 100.0 1.2852 24 666 20.2 332.09
## 125 20.0 3.97 0 0.6470 8.398 91.5 2.2885 5 264 13.0 386.86
## 126 0.0 10.01 0 0.5470 6.715 81.6 2.6775 6 432 17.8 395.59
## 127 0.0 18.10 0 0.6680 4.138 100.0 1.1370 24 666 20.2 396.90
## 128 0.0 5.19 0 0.5150 5.968 58.5 4.8122 5 224 20.2 396.90
## 129 0.0 8.56 0 0.5200 5.836 91.9 2.2110 5 384 20.9 395.67
## 130 0.0 13.92 0 0.4370 6.549 51.0 5.9604 4 289 16.0 392.85
## 131 0.0 18.10 0 0.6710 6.968 91.9 1.4165 24 666 20.2 396.90
## 132 0.0 18.10 1 0.7700 5.803 89.0 1.9047 24 666 20.2 353.04
## 133 25.0 4.86 0 0.4260 6.302 32.2 5.4007 4 281 19.0 396.90
## 134 0.0 18.10 0 0.5800 5.713 56.7 2.8237 24 666 20.2 396.90
## 135 90.0 1.21 1 0.4010 7.923 24.8 5.8850 1 198 13.6 395.52
## 136 0.0 2.89 0 0.4450 6.625 57.8 3.4952 2 276 18.0 357.98
## 137 12.5 7.87 0 0.5240 5.631 100.0 6.0821 5 311 15.2 386.63
## 138 0.0 8.14 0 0.5380 5.935 29.3 4.4986 4 307 21.0 386.85
## 139 0.0 21.89 0 0.6240 6.174 93.6 1.6119 4 437 21.2 388.08
## 140 30.0 4.93 0 0.4280 6.606 42.2 6.1899 6 300 16.6 383.78
## 141 0.0 6.91 0 0.4480 6.069 40.0 5.7209 3 233 17.9 389.39
## 142 0.0 5.96 0 0.4990 5.841 61.4 3.3779 5 279 19.2 377.56
## 143 0.0 19.58 1 0.6050 8.375 93.9 2.1620 5 403 14.7 388.45
## 144 0.0 21.89 0 0.6240 6.335 98.2 2.1107 4 437 21.2 394.67
## 145 0.0 9.69 0 0.5850 5.569 73.5 2.3999 6 391 19.2 395.77
## 146 0.0 6.20 0 0.5040 8.266 78.3 2.8944 8 307 17.4 385.05
## 147 0.0 21.89 0 0.6240 5.019 100.0 1.4394 4 437 21.2 396.90
## 148 0.0 6.20 0 0.5040 7.163 79.9 3.2157 8 307 17.4 372.08
## 149 0.0 18.10 0 0.7000 5.277 98.1 1.4261 24 666 20.2 396.90
## 150 12.5 6.07 0 0.4090 5.885 33.0 6.4980 4 345 18.9 396.90
## 151 0.0 18.10 0 0.7400 6.629 94.6 2.1247 24 666 20.2 109.85
## 152 34.0 6.09 0 0.4330 6.495 18.4 5.4917 7 329 16.1 383.61
## 153 0.0 10.59 1 0.4890 5.807 53.8 3.6526 4 277 18.6 390.94
## 154 0.0 27.74 0 0.6090 5.093 98.0 1.8226 4 711 20.1 318.43
## 155 0.0 19.58 0 0.6050 6.319 96.1 2.1000 5 403 14.7 297.09
## 156 40.0 6.41 1 0.4470 6.758 32.9 4.0776 4 254 17.6 396.90
## 157 0.0 18.10 0 0.7180 6.824 76.5 1.7940 24 666 20.2 48.45
## 158 82.5 2.03 0 0.4150 7.610 15.7 6.2700 2 348 14.7 395.38
## 159 0.0 8.56 0 0.5200 6.405 85.4 2.7147 5 384 20.9 70.80
## 160 0.0 19.58 1 0.6050 7.802 98.2 2.0407 5 403 14.7 389.61
## 161 0.0 18.10 0 0.5840 6.162 97.4 2.2060 24 666 20.2 302.76
## 162 0.0 6.20 0 0.5040 8.040 86.5 3.2157 8 307 17.4 387.38
## 163 20.0 3.33 0 0.4429 6.968 37.2 5.2447 5 216 14.9 392.23
## 164 80.0 3.37 0 0.3980 5.787 31.1 6.6115 4 337 16.1 396.90
## 165 0.0 4.05 0 0.5100 5.572 88.5 2.5961 5 296 16.6 396.90
## 166 22.0 5.86 0 0.4310 6.718 17.5 7.8265 7 330 19.1 393.74
## 167 52.5 5.32 0 0.4050 6.315 45.6 7.3172 6 293 16.6 396.90
## 168 0.0 18.10 0 0.6930 5.747 98.9 1.6334 24 666 20.2 393.10
## 169 0.0 18.10 0 0.6790 5.304 89.1 1.6475 24 666 20.2 127.36
## 170 0.0 18.10 1 0.7700 6.395 91.0 2.5052 24 666 20.2 391.34
## 171 75.0 2.95 0 0.4280 6.595 21.8 5.4011 3 252 18.3 395.63
## 172 0.0 19.58 0 0.8710 5.272 94.0 1.7364 5 403 14.7 88.63
## 173 0.0 8.14 0 0.5380 5.834 56.5 4.4986 4 307 21.0 395.62
## 174 28.0 15.04 0 0.4640 6.211 28.9 3.6659 4 270 18.2 396.33
## 175 20.0 3.97 0 0.6470 7.327 94.5 2.0788 5 264 13.0 393.42
## 176 0.0 18.10 0 0.5840 5.837 59.7 1.9976 24 666 20.2 24.65
## 177 0.0 18.10 0 0.7180 4.963 91.4 1.7523 24 666 20.2 316.03
## 178 0.0 12.83 0 0.4370 5.874 36.6 4.5026 5 398 18.7 396.06
## 179 0.0 18.10 0 0.7000 4.368 91.2 1.4395 24 666 20.2 285.83
## 180 20.0 3.97 0 0.6470 7.014 84.6 2.1329 5 264 13.0 384.07
## 181 0.0 3.41 0 0.4890 7.079 63.1 3.4145 2 270 17.8 396.06
## 182 30.0 4.93 0 0.4280 6.358 52.9 7.0355 6 300 16.6 372.75
## 183 0.0 18.10 0 0.7000 6.051 82.5 2.1678 24 666 20.2 378.38
## 184 90.0 1.22 0 0.4030 7.249 21.9 8.6966 5 226 17.9 395.93
## 185 0.0 2.46 0 0.4880 5.604 89.8 2.9879 3 193 17.8 391.00
## 186 0.0 8.56 0 0.5200 6.727 79.9 2.7778 5 384 20.9 394.76
## 187 90.0 3.75 0 0.3940 7.454 34.2 6.3361 3 244 15.9 386.34
## 188 0.0 18.10 0 0.7130 6.297 91.8 2.3682 24 666 20.2 385.09
## 189 0.0 18.10 1 0.7180 8.780 82.9 1.9047 24 666 20.2 354.55
## 190 0.0 18.10 0 0.5320 6.750 74.9 3.3317 24 666 20.2 393.07
## 191 55.0 3.78 0 0.4840 6.696 56.4 5.7321 5 370 17.6 396.90
## 192 0.0 7.38 0 0.4930 6.431 14.7 5.4159 5 287 19.6 393.68
## 193 20.0 6.96 0 0.4640 6.240 16.3 4.4290 3 223 18.6 396.90
## 194 0.0 18.10 0 0.7400 6.152 100.0 1.9142 24 666 20.2 9.32
## 195 0.0 19.58 1 0.8710 5.012 88.0 1.6102 5 403 14.7 343.28
## 196 0.0 6.91 0 0.4480 6.211 6.5 5.7209 3 233 17.9 394.46
## 197 0.0 11.93 0 0.5730 6.593 69.1 2.4786 1 273 21.0 391.99
## 198 0.0 18.10 0 0.7400 6.251 96.6 2.1980 24 666 20.2 388.52
## 199 0.0 18.10 0 0.5970 6.657 100.0 1.5275 24 666 20.2 35.05
## 200 20.0 3.97 0 0.6470 7.206 91.6 1.9301 5 264 13.0 387.89
## 201 80.0 3.37 0 0.3980 6.290 17.8 6.6115 4 337 16.1 396.90
## 202 0.0 19.58 0 0.8710 5.186 93.8 1.5296 5 403 14.7 356.99
## 203 0.0 18.10 0 0.6790 5.957 100.0 1.8026 24 666 20.2 16.45
## 204 0.0 21.89 0 0.6240 6.151 97.9 1.6687 4 437 21.2 396.90
## 205 25.0 5.13 0 0.4530 6.762 43.4 7.9809 8 284 19.7 395.58
## 206 0.0 8.14 0 0.5380 5.813 100.0 4.0952 4 307 21.0 394.54
## 207 70.0 2.24 0 0.4000 6.345 20.1 7.8278 5 358 14.8 368.24
## 208 20.0 6.96 1 0.4640 7.691 51.8 4.3665 3 223 18.6 390.77
## 209 22.0 5.86 0 0.4310 6.226 79.2 8.0555 7 330 19.1 376.14
## 210 0.0 13.89 1 0.5500 5.951 93.8 2.8893 5 276 16.4 396.90
## 211 0.0 18.10 0 0.6710 6.380 96.2 1.3861 24 666 20.2 396.90
## 212 0.0 9.69 0 0.5850 5.707 54.0 2.3817 6 391 19.2 396.90
## 213 0.0 21.89 0 0.6240 5.942 93.5 1.9669 4 437 21.2 378.25
## 214 0.0 25.65 0 0.5810 5.879 95.8 2.0063 2 188 19.1 379.38
## 215 0.0 18.10 0 0.7000 4.880 100.0 1.5895 24 666 20.2 372.92
## 216 0.0 5.19 0 0.5150 6.310 38.5 6.4584 5 224 20.2 389.40
## 217 0.0 18.10 0 0.5840 6.003 94.5 2.5403 24 666 20.2 331.29
## 218 20.0 3.97 0 0.5750 7.470 52.6 2.8720 5 264 13.0 390.30
## 219 0.0 18.10 0 0.6140 6.484 93.6 2.3053 24 666 20.2 396.21
## 220 12.5 6.07 0 0.4090 5.878 21.4 6.4980 4 345 18.9 396.21
## 221 20.0 3.97 0 0.6470 7.333 100.0 1.8946 5 264 13.0 383.29
## 222 0.0 9.90 0 0.5440 6.023 90.4 2.8340 4 304 18.4 396.30
## 223 35.0 1.52 0 0.4420 7.241 49.3 7.0379 1 284 15.5 394.74
## 224 20.0 3.97 0 0.6470 8.704 86.9 1.8010 5 264 13.0 389.70
## 225 0.0 6.20 0 0.5070 7.358 71.6 4.1480 8 307 17.4 390.07
## 226 0.0 13.92 0 0.4370 5.790 58.0 6.3200 4 289 16.0 396.90
## 227 0.0 27.74 0 0.6090 5.454 92.7 1.8209 4 711 20.1 395.09
## 228 0.0 6.20 0 0.5070 8.337 73.3 3.8384 8 307 17.4 385.91
## 229 0.0 8.14 0 0.5380 6.072 100.0 4.1750 4 307 21.0 376.73
## 230 0.0 18.10 0 0.7130 6.317 83.0 2.7344 24 666 20.2 396.90
## 231 0.0 18.10 0 0.6550 5.759 48.2 3.0665 24 666 20.2 334.40
## 232 0.0 18.10 0 0.7130 7.393 99.3 2.4527 24 666 20.2 375.87
## 233 0.0 7.38 0 0.4930 5.708 74.3 4.7211 5 287 19.6 391.13
## 234 0.0 18.10 0 0.5830 6.114 79.8 3.5459 24 666 20.2 392.68
## 235 0.0 13.89 1 0.5500 6.373 92.4 3.3633 5 276 16.4 393.74
## 236 95.0 1.47 0 0.4030 7.135 13.9 7.6534 3 402 17.0 384.30
## 237 80.0 1.91 0 0.4130 5.936 19.5 10.5857 4 334 22.0 376.04
## 238 34.0 6.09 0 0.4330 6.982 17.7 5.4917 7 329 16.1 390.43
## 239 0.0 4.05 0 0.5100 6.020 47.2 3.5549 5 296 16.6 393.23
## 240 0.0 21.89 0 0.6240 5.857 98.2 1.6686 4 437 21.2 392.04
## 241 0.0 18.10 0 0.7400 6.406 97.2 2.0651 24 666 20.2 385.96
## 242 0.0 9.90 0 0.5440 5.914 83.2 3.9986 4 304 18.4 390.70
## 243 0.0 19.58 0 0.8710 5.628 100.0 1.5166 5 403 14.7 169.27
## 244 0.0 18.10 0 0.7130 6.436 87.9 2.3158 24 666 20.2 100.19
## 245 40.0 6.41 0 0.4470 6.482 32.1 4.1403 4 254 17.6 396.90
## 246 0.0 25.65 0 0.5810 5.870 69.7 2.2577 2 188 19.1 389.15
## 247 0.0 18.10 0 0.7180 6.006 95.3 1.8746 24 666 20.2 319.98
## 248 0.0 19.58 0 0.8710 4.926 95.7 1.4608 5 403 14.7 391.71
## 249 0.0 8.56 0 0.5200 6.229 91.2 2.5451 5 384 20.9 391.23
## 250 0.0 10.81 0 0.4130 5.961 17.5 5.2873 4 305 19.2 376.94
## 251 20.0 3.33 0 0.4429 6.812 32.2 4.1007 5 216 14.9 396.90
## 252 0.0 2.46 0 0.4880 6.563 95.6 2.8470 3 193 17.8 396.90
## 253 0.0 18.10 0 0.7700 6.112 81.3 2.5091 24 666 20.2 390.74
## 254 95.0 1.47 0 0.4030 6.975 15.3 7.6534 3 402 17.0 396.90
## 255 20.0 3.97 0 0.6470 7.203 81.8 2.1121 5 264 13.0 392.80
## 256 0.0 18.10 0 0.6930 5.987 100.0 1.5888 24 666 20.2 396.90
## 257 0.0 25.65 0 0.5810 6.004 84.1 2.1974 2 188 19.1 377.67
## 258 0.0 2.89 0 0.4450 8.069 76.0 3.4952 2 276 18.0 396.90
## 259 12.5 6.07 0 0.4090 5.594 36.8 6.4980 4 345 18.9 396.90
## 260 0.0 19.58 0 0.8710 4.903 97.8 1.3459 5 403 14.7 396.90
## 261 40.0 6.41 1 0.4470 6.826 27.6 4.8628 4 254 17.6 393.45
## 262 22.0 5.86 0 0.4310 6.487 13.0 7.3967 7 330 19.1 396.28
## 263 0.0 9.69 0 0.5850 5.926 42.6 2.3817 6 391 19.2 396.90
## 264 0.0 10.01 0 0.5470 5.928 88.2 2.4631 6 432 17.8 344.91
## 265 0.0 19.58 0 0.8710 6.130 100.0 1.4191 5 403 14.7 172.91
## 266 0.0 3.41 0 0.4890 7.007 86.3 3.4217 2 270 17.8 396.90
## 267 0.0 19.58 0 0.8710 6.122 97.3 1.6180 5 403 14.7 372.80
## 268 0.0 19.58 0 0.8710 5.468 100.0 1.4118 5 403 14.7 396.90
## 269 0.0 18.10 0 0.7700 6.398 88.0 2.5182 24 666 20.2 374.56
## 270 0.0 11.93 0 0.5730 6.030 80.8 2.5050 1 273 21.0 396.90
## 271 0.0 18.10 0 0.7130 6.417 98.3 2.1850 24 666 20.2 304.21
## 272 0.0 18.10 0 0.6590 4.138 100.0 1.1781 24 666 20.2 370.22
## 273 0.0 21.89 0 0.6240 5.822 95.4 2.4699 4 437 21.2 388.69
## 274 0.0 4.05 0 0.5100 6.546 33.1 3.1323 5 296 16.6 390.96
## 275 0.0 25.65 0 0.5810 5.986 88.4 1.9929 2 188 19.1 385.02
## 276 0.0 18.10 0 0.7130 6.513 89.9 2.8016 24 666 20.2 393.82
## 277 0.0 18.10 0 0.7130 5.976 87.9 2.5806 24 666 20.2 10.48
## 278 0.0 8.14 0 0.5380 5.813 90.3 4.6820 4 307 21.0 376.88
## 279 0.0 18.10 0 0.6790 6.202 78.7 1.8629 24 666 20.2 18.82
## 280 22.0 5.86 0 0.4310 6.108 34.9 8.0555 7 330 19.1 390.18
## 281 60.0 1.69 0 0.4110 6.579 35.9 10.7103 4 411 18.3 370.78
## 282 12.5 7.87 0 0.5240 5.889 39.0 5.4509 5 311 15.2 390.50
## 283 0.0 21.89 0 0.6240 6.326 97.7 2.2710 4 437 21.2 396.90
## 284 0.0 18.10 0 0.7130 6.301 83.7 2.7831 24 666 20.2 272.21
## 285 0.0 10.81 0 0.4130 6.065 7.8 5.2873 4 305 19.2 390.91
## 286 0.0 18.10 0 0.5970 5.757 100.0 1.4130 24 666 20.2 2.60
## 287 0.0 9.90 0 0.5440 6.266 82.8 3.2628 4 304 18.4 393.39
## 288 0.0 10.01 0 0.5470 6.254 84.2 2.2565 6 432 17.8 388.74
## 289 0.0 18.10 0 0.7000 5.536 100.0 1.5804 24 666 20.2 396.90
## 290 0.0 18.10 0 0.6930 6.405 96.0 1.6768 24 666 20.2 396.90
## 291 0.0 19.58 0 0.6050 5.854 91.8 2.4220 5 403 14.7 395.11
## 292 0.0 8.14 0 0.5380 5.727 69.5 3.7965 4 307 21.0 390.95
## 293 0.0 6.20 1 0.5070 6.951 88.5 2.8617 8 307 17.4 391.70
## 294 0.0 4.49 0 0.4490 6.015 45.1 4.4272 3 247 18.5 395.99
## 295 0.0 27.74 0 0.6090 5.983 83.5 2.1099 4 711 20.1 396.90
## 296 0.0 18.10 1 0.7700 6.212 97.4 2.1222 24 666 20.2 377.73
## 297 0.0 7.38 0 0.4930 6.041 49.9 4.7211 5 287 19.6 396.90
## 298 0.0 18.10 0 0.6310 4.970 100.0 1.3325 24 666 20.2 375.52
## 299 40.0 6.41 1 0.4470 7.267 49.0 4.7872 4 254 17.6 389.25
## 300 0.0 6.91 0 0.4480 6.770 2.9 5.7209 3 233 17.9 385.41
## 301 40.0 6.41 0 0.4470 6.854 42.8 4.2673 4 254 17.6 396.90
## 302 0.0 10.59 0 0.4890 6.182 42.4 3.9454 4 277 18.6 393.63
## 303 0.0 10.59 1 0.4890 6.064 59.1 4.2392 4 277 18.6 381.32
## 304 0.0 9.69 0 0.5850 5.670 28.8 2.7986 6 391 19.2 393.29
## 305 0.0 9.90 0 0.5440 6.635 82.5 3.3175 4 304 18.4 396.90
## 306 33.0 2.18 0 0.4720 7.236 41.1 4.0220 7 222 18.4 393.68
## 307 0.0 21.89 0 0.6240 6.431 98.8 1.8125 4 437 21.2 396.90
## 308 0.0 18.10 0 0.7130 6.081 84.4 2.7175 24 666 20.2 396.90
## 309 30.0 4.93 0 0.4280 6.897 54.3 6.3361 6 300 16.6 391.25
## 310 20.0 6.96 0 0.4640 6.538 58.7 3.9175 3 223 18.6 394.96
## 311 0.0 10.59 0 0.4890 5.891 22.3 3.9454 4 277 18.6 396.90
## 312 0.0 18.10 0 0.6930 6.193 92.6 1.7912 24 666 20.2 396.90
## 313 0.0 4.05 0 0.5100 6.315 73.4 3.3175 5 296 16.6 395.60
## 314 0.0 4.49 0 0.4490 6.389 48.0 4.7794 3 247 18.5 396.90
## 315 0.0 21.89 0 0.6240 6.372 97.9 2.3274 4 437 21.2 385.76
## 316 0.0 10.01 0 0.5470 6.021 82.6 2.7474 6 432 17.8 394.51
## 317 40.0 1.25 0 0.4290 6.939 34.5 8.7921 1 335 19.7 389.85
## 318 0.0 2.46 0 0.4880 6.144 62.2 2.5979 3 193 17.8 396.90
## 319 0.0 7.38 0 0.4930 6.426 52.3 4.5404 5 287 19.6 396.90
## 320 0.0 18.10 0 0.6930 6.343 100.0 1.5741 24 666 20.2 396.90
## 321 0.0 6.20 1 0.5070 6.879 77.7 3.2721 8 307 17.4 390.39
## 322 20.0 3.97 0 0.6470 7.520 89.4 2.1398 5 264 13.0 388.37
## 323 0.0 18.10 0 0.5970 6.852 100.0 1.4655 24 666 20.2 179.36
## 324 30.0 4.93 0 0.4280 6.095 65.1 6.3361 6 300 16.6 394.62
## 325 0.0 9.90 0 0.5440 6.113 58.8 4.0019 4 304 18.4 396.23
## 326 0.0 13.92 0 0.4370 6.127 18.4 5.5027 4 289 16.0 396.90
## 327 75.0 2.95 0 0.4280 7.024 15.8 5.4011 3 252 18.3 395.62
## 328 80.0 1.52 0 0.4040 7.107 36.6 7.3090 2 329 12.6 354.31
## 329 0.0 8.14 0 0.5380 6.096 96.9 3.7598 4 307 21.0 248.31
## 330 22.0 5.86 0 0.4310 5.605 70.2 7.9549 7 330 19.1 389.13
## 331 0.0 18.10 0 0.7130 6.749 92.6 2.3236 24 666 20.2 0.32
## 332 12.5 7.87 0 0.5240 6.377 94.3 6.3467 5 311 15.2 392.52
## 333 0.0 8.14 0 0.5380 6.142 91.7 3.9769 4 307 21.0 396.90
## 334 35.0 6.06 0 0.4379 6.031 23.3 6.6407 1 304 16.9 362.25
## 335 0.0 18.10 0 0.6930 5.349 96.0 1.7028 24 666 20.2 396.90
## 336 0.0 18.10 0 0.5800 6.437 75.0 2.8965 24 666 20.2 393.37
## 337 80.0 3.64 0 0.3920 6.108 32.0 9.2203 1 315 16.4 392.89
## 338 20.0 6.96 0 0.4640 5.856 42.1 4.4290 3 223 18.6 388.65
## 339 0.0 12.83 0 0.4370 6.140 45.8 4.0905 5 398 18.7 386.96
## 340 0.0 9.90 0 0.5440 6.567 87.3 3.6023 4 304 18.4 395.69
## 341 0.0 19.58 0 0.8710 6.510 100.0 1.7659 5 403 14.7 364.31
## 342 0.0 2.46 0 0.4880 7.765 83.3 2.7410 3 193 17.8 395.56
## 343 80.0 0.46 0 0.4220 7.875 32.0 5.6484 4 255 14.4 394.23
## 344 0.0 18.10 0 0.6310 3.863 100.0 1.5106 24 666 20.2 131.42
## 345 21.0 5.64 0 0.4390 6.511 21.1 6.8147 4 243 16.8 396.90
## 346 0.0 8.14 0 0.5380 5.599 85.7 4.4546 4 307 21.0 303.42
## 347 0.0 18.10 0 0.6930 5.683 100.0 1.4254 24 666 20.2 384.97
## 348 0.0 2.18 0 0.4580 7.147 54.2 6.0622 3 222 18.7 396.90
## 349 21.0 5.64 0 0.4390 6.115 63.0 6.8147 4 243 16.8 393.97
## 350 20.0 6.96 1 0.4640 5.920 61.5 3.9175 3 223 18.6 391.34
## 351 95.0 2.68 0 0.4161 7.853 33.2 5.1180 4 224 14.7 392.78
## 352 12.5 7.87 0 0.5240 6.012 66.6 5.5605 5 311 15.2 395.60
## 353 0.0 25.65 0 0.5810 5.961 92.9 2.0869 2 188 19.1 378.09
## 354 0.0 10.59 1 0.4890 5.404 88.6 3.6650 4 277 18.6 395.24
## 355 0.0 8.56 0 0.5200 6.137 87.4 2.7147 5 384 20.9 394.47
## 356 33.0 2.18 0 0.4720 6.849 70.3 3.1827 7 222 18.4 396.90
## 357 0.0 10.01 0 0.5470 5.731 65.2 2.7592 6 432 17.8 391.50
## 358 20.0 3.97 0 0.6470 6.842 100.0 2.0107 5 264 13.0 391.93
## 359 0.0 18.10 0 0.5840 5.427 95.4 2.4298 24 666 20.2 352.58
## 360 28.0 15.04 0 0.4640 6.249 77.3 3.6150 4 270 18.2 396.90
## 361 0.0 6.91 0 0.4480 5.399 95.3 5.8700 3 233 17.9 396.90
## 362 85.0 4.15 0 0.4290 6.516 27.7 8.5353 4 351 17.9 392.43
## 363 0.0 8.56 0 0.5200 6.127 85.2 2.1224 5 384 20.9 387.69
## 364 0.0 3.41 0 0.4890 6.405 73.9 3.0921 2 270 17.8 393.55
## 365 0.0 18.10 0 0.7700 5.362 96.2 2.1036 24 666 20.2 380.79
## 366 0.0 10.59 0 0.4890 5.783 72.7 4.3549 4 277 18.6 389.43
## 367 0.0 9.69 0 0.5850 6.027 79.7 2.4982 6 391 19.2 396.90
## 368 0.0 18.10 0 0.6790 6.434 100.0 1.8347 24 666 20.2 27.25
## 369 0.0 21.89 0 0.6240 6.458 98.9 2.1185 4 437 21.2 395.04
## 370 0.0 10.01 0 0.5470 5.872 73.1 2.4775 6 432 17.8 338.63
## 371 0.0 18.10 0 0.6140 6.103 85.1 2.0218 24 666 20.2 2.52
## 372 21.0 5.64 0 0.4390 5.998 21.4 6.8147 4 243 16.8 396.90
## 373 0.0 18.10 0 0.6140 5.648 87.6 1.9512 24 666 20.2 291.55
## 374 22.0 5.86 0 0.4310 5.593 76.5 7.9549 7 330 19.1 372.49
## 375 0.0 18.10 0 0.7000 5.520 100.0 1.5331 24 666 20.2 396.90
## 376 0.0 18.10 0 0.7130 6.728 94.1 2.4961 24 666 20.2 6.68
## 377 0.0 18.10 0 0.7000 5.713 97.0 1.9265 24 666 20.2 394.43
## 378 52.5 5.32 0 0.4050 6.565 22.9 7.3172 6 293 16.6 371.72
## 379 0.0 18.10 0 0.7000 4.652 100.0 1.4672 24 666 20.2 396.90
## 380 34.0 6.09 0 0.4330 6.590 40.4 5.4917 7 329 16.1 395.75
## 381 0.0 10.59 0 0.4890 6.375 32.3 3.9454 4 277 18.6 385.81
## 382 0.0 6.20 0 0.5040 7.686 17.0 3.3751 8 307 17.4 377.51
## 383 0.0 12.83 0 0.4370 6.279 74.5 4.0522 5 398 18.7 373.66
## 384 0.0 18.10 0 0.6930 5.887 94.7 1.7821 24 666 20.2 396.90
## 385 0.0 18.10 0 0.6710 6.223 100.0 1.3861 24 666 20.2 393.74
## 386 0.0 18.10 1 0.7700 6.127 83.4 2.7227 24 666 20.2 395.43
## 387 0.0 18.10 0 0.5800 6.167 84.0 3.0334 24 666 20.2 396.90
## 388 0.0 27.74 0 0.6090 5.983 98.8 1.8681 4 711 20.1 390.11
## 389 0.0 4.39 0 0.4420 6.014 48.5 8.0136 3 352 18.8 385.64
## 390 0.0 6.20 1 0.5070 6.164 91.3 3.0480 8 307 17.4 395.24
## 391 0.0 10.81 0 0.4130 6.417 6.6 5.2873 4 305 19.2 383.73
## 392 0.0 4.05 0 0.5100 6.860 74.4 2.9153 5 296 16.6 391.27
## 393 0.0 18.10 0 0.7130 6.185 98.7 2.2616 24 666 20.2 396.90
## 394 0.0 6.91 0 0.4480 5.602 62.0 6.0877 3 233 17.9 396.90
## 395 0.0 18.10 1 0.6310 6.683 96.8 1.3567 24 666 20.2 375.33
## 396 90.0 2.02 0 0.4100 6.728 36.1 12.1265 5 187 17.0 384.46
## 397 0.0 13.92 0 0.4370 6.009 42.3 5.5027 4 289 16.0 396.90
## 398 0.0 18.10 0 0.6930 6.404 100.0 1.6390 24 666 20.2 376.11
## 399 0.0 18.10 0 0.5830 5.905 53.2 3.1523 24 666 20.2 388.22
## 400 0.0 19.58 1 0.8710 6.152 82.6 1.7455 5 403 14.7 88.01
## 401 0.0 18.10 0 0.5800 5.926 71.0 2.9084 24 666 20.2 368.74
## 402 45.0 3.44 0 0.4370 6.739 30.8 6.4798 5 398 15.2 389.71
## 403 0.0 18.10 0 0.5830 5.871 41.9 3.7240 24 666 20.2 370.73
## 404 0.0 12.83 0 0.4370 6.273 6.0 4.2515 5 398 18.7 394.92
## 405 0.0 18.10 0 0.5840 6.833 94.3 2.0882 24 666 20.2 81.33
## 406 0.0 4.05 0 0.5100 6.416 84.1 2.6463 5 296 16.6 395.50
## 407 45.0 3.44 0 0.4370 7.178 26.3 6.4798 5 398 15.2 390.49
## 408 85.0 0.74 0 0.4100 6.383 35.7 9.1876 2 313 17.3 396.90
## 409 0.0 18.10 0 0.5840 5.565 70.6 2.0635 24 666 20.2 3.65
## 410 0.0 8.56 0 0.5200 6.195 54.4 2.7778 5 384 20.9 393.49
## 411 0.0 9.90 0 0.5440 5.705 77.7 3.9450 4 304 18.4 396.42
## 412 0.0 6.91 0 0.4480 5.786 33.3 5.1004 3 233 17.9 396.90
## 413 22.0 5.86 0 0.4310 6.433 49.1 7.8265 7 330 19.1 374.71
## 414 0.0 11.93 0 0.5730 6.120 76.7 2.2875 1 273 21.0 396.90
## 415 0.0 8.56 0 0.5200 5.851 96.7 2.1069 5 384 20.9 394.05
## 416 70.0 2.24 0 0.4000 6.871 47.4 7.8278 5 358 14.8 390.86
## 417 28.0 15.04 0 0.4640 6.442 53.6 3.6659 4 270 18.2 395.01
## 418 0.0 10.01 0 0.5470 6.092 95.4 2.5480 6 432 17.8 396.90
## 419 0.0 19.58 0 0.6050 6.066 100.0 1.7573 5 403 14.7 353.89
## 420 0.0 2.46 0 0.4880 6.980 58.4 2.8290 3 193 17.8 396.90
## 421 60.0 1.69 0 0.4110 5.884 18.5 10.7103 4 411 18.3 392.33
## 422 0.0 19.58 1 0.6050 6.250 92.6 1.7984 5 403 14.7 338.92
## 423 0.0 19.58 0 0.6050 7.489 90.8 1.9709 5 403 14.7 374.43
## 424 0.0 8.14 0 0.5380 5.570 98.1 3.7979 4 307 21.0 376.57
## 425 0.0 8.14 0 0.5380 5.701 95.0 3.7872 4 307 21.0 358.77
## 426 25.0 5.13 0 0.4530 5.927 47.2 6.9320 8 284 19.7 396.90
## 427 0.0 19.58 0 0.8710 5.404 100.0 1.5916 5 403 14.7 341.60
## 428 0.0 19.58 1 0.8710 6.129 96.0 1.7494 5 403 14.7 321.02
## 429 0.0 18.10 0 0.6710 7.313 97.9 1.3163 24 666 20.2 396.90
## 430 0.0 18.10 0 0.7130 6.655 98.2 2.3552 24 666 20.2 355.29
## 431 17.5 1.38 0 0.4161 7.104 59.5 9.2229 3 216 18.6 393.24
## 432 80.0 1.52 0 0.4040 7.287 34.1 7.3090 2 329 12.6 396.90
## 433 0.0 9.69 0 0.5850 6.019 65.3 2.4091 6 391 19.2 396.90
## 434 0.0 5.96 0 0.4990 5.966 30.2 3.8473 5 279 19.2 393.43
## 435 45.0 3.44 0 0.4370 7.185 38.9 4.5667 5 398 15.2 396.90
## 436 0.0 8.14 0 0.5380 6.047 88.8 4.4534 4 307 21.0 306.38
## 437 45.0 3.44 0 0.4370 6.556 29.1 4.5667 5 398 15.2 382.84
## 438 0.0 18.10 0 0.6930 5.852 77.8 1.5004 24 666 20.2 338.16
## 439 95.0 2.68 0 0.4161 8.034 31.9 5.1180 4 224 14.7 390.55
## 440 0.0 8.14 0 0.5380 5.456 36.6 3.7965 4 307 21.0 288.99
## 441 0.0 13.92 0 0.4370 6.678 31.1 5.9604 4 289 16.0 396.90
## 442 0.0 18.10 0 0.7130 6.701 90.0 2.5975 24 666 20.2 255.23
## 443 0.0 18.10 0 0.5320 5.762 40.3 4.0983 24 666 20.2 392.92
## 444 80.0 1.52 0 0.4040 7.274 38.3 7.3090 2 329 12.6 392.20
## 445 0.0 3.41 0 0.4890 6.417 66.1 3.0923 2 270 17.8 392.18
## 446 80.0 4.95 0 0.4110 7.148 27.7 5.1167 4 245 19.2 396.90
## 447 0.0 18.10 0 0.5970 5.617 97.9 1.4547 24 666 20.2 314.64
## 448 60.0 2.93 0 0.4010 6.800 9.9 6.2196 1 265 15.6 393.37
## 449 0.0 18.10 0 0.7400 6.341 96.4 2.0720 24 666 20.2 318.01
## 450 0.0 18.10 0 0.6140 6.980 67.6 2.5329 24 666 20.2 374.68
## 451 0.0 18.10 0 0.6680 4.906 100.0 1.1742 24 666 20.2 396.90
## 452 0.0 8.14 0 0.5380 5.965 89.2 4.0123 4 307 21.0 392.53
## 453 33.0 2.18 0 0.4720 7.420 71.9 3.0992 7 222 18.4 396.90
## 454 0.0 18.10 0 0.6930 5.531 85.4 1.6074 24 666 20.2 329.46
## 455 0.0 8.14 0 0.5380 5.924 94.1 4.3996 4 307 21.0 394.33
## 456 25.0 4.86 0 0.4260 6.619 70.4 5.4007 4 281 19.0 395.63
## 457 0.0 10.59 0 0.4890 5.412 9.8 3.5875 4 277 18.6 348.93
## 458 12.5 7.87 0 0.5240 6.172 96.1 5.9505 5 311 15.2 396.90
## 459 0.0 18.10 1 0.6680 5.875 89.6 1.1296 24 666 20.2 347.88
## 460 0.0 6.20 0 0.5070 6.086 61.5 3.6519 8 307 17.4 376.75
## 461 0.0 18.10 0 0.7130 5.936 80.3 2.7792 24 666 20.2 3.50
## 462 0.0 18.10 0 0.7130 6.208 95.0 2.2222 24 666 20.2 100.63
## 463 0.0 18.10 0 0.6790 6.193 78.1 1.9356 24 666 20.2 96.73
## 464 0.0 18.10 0 0.5840 6.425 74.8 2.2004 24 666 20.2 97.95
## 465 0.0 12.83 0 0.4370 6.232 53.7 5.0141 5 398 18.7 386.40
## 466 0.0 18.10 0 0.7000 5.036 97.0 1.7700 24 666 20.2 396.90
## lstat medv target scored_target
## 1 3.70 50.0 1 1
## 2 26.82 13.4 1 1
## 3 18.85 15.4 1 1
## 4 5.19 23.7 0 0
## 5 4.82 37.9 0 0
## 6 7.67 26.5 0 0
## 7 30.59 5.0 1 1
## 8 36.98 7.0 1 1
## 9 5.68 22.2 0 1
## 10 9.25 20.9 0 0
## 11 3.59 24.8 0 0
## 12 8.94 21.4 0 0
## 13 7.01 25.0 1 1
## 14 3.54 42.8 1 0
## 15 13.15 29.6 0 0
## 16 5.21 28.7 0 0
## 17 3.95 31.6 0 0
## 18 10.45 22.8 1 1
## 19 24.39 8.3 1 1
## 20 21.08 10.9 1 1
## 21 9.09 19.8 0 0
## 22 8.05 29.0 1 1
## 23 6.19 33.2 0 0
## 24 4.98 24.0 0 0
## 25 10.36 23.1 1 0
## 26 4.38 29.1 0 0
## 27 9.74 19.0 0 0
## 28 20.85 11.5 1 1
## 29 7.51 22.9 0 0
## 30 6.73 22.2 0 0
## 31 11.65 24.3 1 1
## 32 12.27 19.8 0 0
## 33 3.57 43.8 0 0
## 34 24.08 9.5 1 1
## 35 8.51 20.6 0 0
## 36 4.70 27.9 0 0
## 37 4.45 50.0 0 0
## 38 18.03 14.6 1 1
## 39 12.67 17.2 0 0
## 40 11.32 22.3 1 1
## 41 9.97 19.3 0 0
## 42 23.24 13.9 1 1
## 43 9.64 22.6 0 0
## 44 8.05 18.2 0 0
## 45 13.27 18.9 0 0
## 46 18.80 16.6 0 0
## 47 10.58 21.2 1 1
## 48 15.94 19.8 0 0
## 49 12.87 19.6 1 1
## 50 11.98 21.0 1 1
## 51 8.23 22.0 0 0
## 52 17.10 18.9 0 0
## 53 9.68 18.9 0 0
## 54 8.65 16.5 0 0
## 55 17.19 16.2 1 1
## 56 23.09 20.0 1 0
## 57 3.76 45.4 0 0
## 58 3.01 46.0 0 0
## 59 9.14 21.6 0 0
## 60 31.99 7.4 1 1
## 61 12.14 23.8 1 1
## 62 12.64 16.1 1 0
## 63 23.98 11.8 1 1
## 64 6.68 32.0 0 0
## 65 12.43 17.1 0 0
## 66 8.26 20.4 1 1
## 67 23.97 7.0 0 0
## 68 15.02 16.7 1 1
## 69 21.14 19.7 1 1
## 70 9.54 25.1 1 1
## 71 9.53 50.0 1 1
## 72 12.33 20.1 0 0
## 73 14.43 17.4 1 1
## 74 9.69 28.7 0 1
## 75 24.91 12.0 1 1
## 76 7.54 23.4 0 0
## 77 21.45 15.4 1 1
## 78 13.51 23.3 0 0
## 79 2.94 33.4 0 0
## 80 6.87 23.1 0 0
## 81 16.21 18.8 0 0
## 82 10.74 23.0 1 1
## 83 17.12 13.1 1 1
## 84 3.33 28.5 0 0
## 85 7.44 50.0 1 1
## 86 6.36 23.7 0 0
## 87 4.59 41.3 1 1
## 88 21.24 13.3 1 1
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## 90 13.45 19.7 0 0
## 91 5.29 28.0 0 0
## 92 4.74 29.0 0 0
## 93 25.79 7.5 1 1
## 94 12.79 22.2 0 0
## 95 5.10 37.0 0 0
## 96 13.11 21.4 1 1
## 97 5.98 22.9 0 0
## 98 34.37 17.9 1 1
## 99 18.05 9.6 1 1
## 100 8.01 21.1 0 1
## 101 22.60 12.7 1 1
## 102 10.97 24.4 0 0
## 103 15.79 19.4 1 1
## 104 14.80 18.9 0 0
## 105 20.08 16.3 1 1
## 106 14.19 19.9 1 1
## 107 6.48 22.0 0 0
## 108 4.61 31.2 0 0
## 109 14.59 17.1 1 1
## 110 7.34 22.6 0 0
## 111 4.63 50.0 1 1
## 112 6.86 23.3 0 0
## 113 9.80 19.5 0 1
## 114 7.14 23.2 0 0
## 115 10.21 19.3 0 0
## 116 7.43 24.1 0 0
## 117 17.15 19.0 1 1
## 118 9.97 20.3 1 0
## 119 17.31 15.6 1 1
## 120 7.60 30.1 1 1
## 121 14.67 17.5 1 1
## 122 5.81 25.3 0 0
## 123 5.25 31.7 1 1
## 124 12.13 27.9 1 1
## 125 5.91 48.8 1 1
## 126 10.16 22.8 0 0
## 127 37.97 13.8 1 1
## 128 9.29 18.7 0 0
## 129 18.66 19.5 0 0
## 130 7.39 27.1 0 0
## 131 17.21 10.4 1 1
## 132 14.64 16.8 1 1
## 133 6.72 24.8 0 0
## 134 14.76 20.1 1 1
## 135 3.16 50.0 0 0
## 136 6.65 28.4 0 0
## 137 29.93 16.5 0 0
## 138 6.58 23.1 1 0
## 139 24.16 14.0 1 1
## 140 7.37 23.3 0 0
## 141 9.55 21.2 0 0
## 142 11.41 20.0 0 0
## 143 3.32 50.0 1 1
## 144 16.96 18.1 1 1
## 145 15.10 17.5 0 1
## 146 4.14 44.8 1 1
## 147 34.41 14.4 1 1
## 148 6.36 31.6 1 1
## 149 30.81 7.2 1 1
## 150 8.79 20.9 0 0
## 151 23.27 13.4 1 1
## 152 8.67 26.4 0 0
## 153 16.03 22.4 0 0
## 154 29.68 8.1 0 0
## 155 11.10 23.8 1 1
## 156 3.53 32.4 0 0
## 157 22.74 8.4 1 1
## 158 3.11 42.3 0 0
## 159 10.63 18.6 0 1
## 160 1.92 50.0 1 1
## 161 24.10 13.3 1 1
## 162 3.13 37.6 1 1
## 163 4.59 35.4 0 0
## 164 10.24 19.4 0 0
## 165 14.69 23.1 0 0
## 166 6.56 26.2 0 0
## 167 7.60 22.3 0 0
## 168 19.92 8.5 1 1
## 169 26.64 10.4 1 1
## 170 13.27 21.7 1 1
## 171 4.32 30.8 0 0
## 172 16.14 13.1 1 1
## 173 8.47 19.9 1 1
## 174 6.21 25.0 0 0
## 175 11.25 31.0 1 1
## 176 15.69 10.2 1 1
## 177 14.00 21.9 1 1
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## 182 11.22 22.2 0 0
## 183 18.76 23.2 1 1
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## 185 13.98 26.4 0 0
## 186 9.42 27.5 0 0
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## 189 5.29 21.9 1 1
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## 191 7.18 23.9 0 0
## 192 5.08 24.6 0 0
## 193 6.59 25.2 0 0
## 194 26.45 8.7 1 1
## 195 12.12 15.3 1 1
## 196 7.44 24.7 0 0
## 197 9.67 22.4 0 0
## 198 16.44 12.6 1 1
## 199 21.22 17.2 1 1
## 200 8.10 36.5 1 1
## 201 4.67 23.5 0 0
## 202 28.32 17.8 1 1
## 203 20.62 8.8 1 1
## 204 18.46 17.8 1 1
## 205 9.50 25.0 0 0
## 206 19.88 14.5 1 1
## 207 4.97 22.5 0 0
## 208 6.58 35.2 0 0
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## 211 23.69 13.1 1 1
## 212 12.01 21.8 0 1
## 213 16.90 17.4 1 1
## 214 17.58 18.8 0 0
## 215 30.62 10.2 1 1
## 216 6.75 20.7 0 1
## 217 21.32 19.1 1 1
## 218 3.16 43.5 1 1
## 219 18.68 16.7 1 1
## 220 8.10 22.0 0 0
## 221 7.79 36.0 1 1
## 222 11.72 19.4 1 0
## 223 5.49 32.7 0 0
## 224 5.12 50.0 1 1
## 225 4.73 31.5 1 1
## 226 15.84 20.3 0 0
## 227 18.06 15.2 0 0
## 228 2.47 41.7 1 1
## 229 13.04 14.5 1 1
## 230 13.99 19.5 1 1
## 231 14.13 19.9 1 1
## 232 16.74 17.8 1 1
## 233 11.74 18.5 1 0
## 234 14.98 19.1 1 1
## 235 10.50 23.0 0 1
## 236 4.45 32.9 0 0
## 237 5.57 20.6 0 0
## 238 4.86 33.1 0 0
## 239 10.11 23.2 0 0
## 240 21.32 13.3 0 1
## 241 19.52 17.1 1 1
## 242 18.33 17.8 1 0
## 243 16.65 15.6 1 1
## 244 16.22 14.3 1 1
## 245 7.19 29.1 0 0
## 246 14.37 22.0 0 0
## 247 15.70 14.2 1 1
## 248 29.53 14.6 1 1
## 249 15.55 19.4 1 0
## 250 9.88 21.7 0 0
## 251 4.85 35.1 0 0
## 252 5.68 32.5 0 0
## 253 12.67 22.6 1 1
## 254 4.56 34.9 0 0
## 255 9.59 33.8 1 1
## 256 26.77 5.6 1 1
## 257 14.27 20.3 0 0
## 258 4.21 38.7 0 0
## 259 13.09 17.4 0 0
## 260 29.29 11.8 1 1
## 261 4.16 33.1 0 0
## 262 5.90 24.4 0 0
## 263 13.59 24.5 1 1
## 264 15.76 18.3 0 0
## 265 27.80 13.8 1 1
## 266 5.50 23.6 0 0
## 267 14.10 21.5 1 1
## 268 26.42 15.6 1 1
## 269 7.79 25.0 1 1
## 270 7.88 11.9 0 0
## 271 19.31 13.0 1 1
## 272 23.34 11.9 1 1
## 273 15.03 18.4 1 1
## 274 5.33 29.4 0 0
## 275 14.81 21.4 0 0
## 276 10.29 20.2 1 1
## 277 19.01 12.7 1 1
## 278 14.81 16.6 1 1
## 279 14.52 10.9 1 1
## 280 9.16 24.3 1 0
## 281 5.49 24.1 0 0
## 282 15.71 21.7 0 0
## 283 12.26 19.6 1 1
## 284 16.23 14.9 1 1
## 285 5.52 22.8 0 0
## 286 10.11 15.0 1 1
## 287 7.90 21.6 1 0
## 288 10.45 18.5 0 0
## 289 23.60 11.3 1 1
## 290 19.37 12.5 1 1
## 291 11.64 22.7 1 1
## 292 11.28 18.2 1 0
## 293 9.71 26.7 1 1
## 294 12.86 22.5 0 0
## 295 13.35 20.1 0 0
## 296 17.60 17.8 1 1
## 297 7.70 20.4 1 0
## 298 3.26 50.0 1 1
## 299 6.05 33.2 0 0
## 300 4.84 26.6 0 0
## 301 2.98 32.0 0 0
## 302 9.47 25.0 0 0
## 303 14.66 24.4 0 0
## 304 17.60 23.1 0 1
## 305 4.54 22.8 1 0
## 306 6.93 36.1 0 0
## 307 15.39 18.0 1 1
## 308 14.70 20.0 1 1
## 309 11.38 22.0 0 0
## 310 7.73 24.4 0 0
## 311 10.87 22.6 0 0
## 312 15.17 13.8 1 1
## 313 6.29 24.6 0 0
## 314 9.62 23.9 0 0
## 315 11.12 23.0 1 1
## 316 10.30 19.2 0 0
## 317 5.89 26.6 0 0
## 318 9.45 36.2 0 0
## 319 7.20 23.8 0 0
## 320 20.32 7.2 1 1
## 321 9.93 27.5 1 1
## 322 7.26 43.1 1 1
## 323 19.78 27.5 1 1
## 324 12.40 20.1 0 0
## 325 12.73 21.0 1 0
## 326 8.58 23.9 0 0
## 327 1.98 34.9 0 0
## 328 8.61 30.3 0 0
## 329 20.34 13.5 1 1
## 330 18.46 18.5 0 0
## 331 17.44 13.4 1 1
## 332 20.45 15.0 0 0
## 333 18.72 15.2 1 1
## 334 7.83 19.4 0 0
## 335 19.77 8.3 1 1
## 336 14.36 23.2 1 1
## 337 6.57 21.9 0 0
## 338 13.00 21.1 1 0
## 339 10.27 20.8 0 0
## 340 9.28 23.8 1 0
## 341 7.39 23.3 1 1
## 342 7.56 39.8 0 0
## 343 2.97 50.0 0 0
## 344 13.33 23.1 1 1
## 345 5.28 25.0 0 0
## 346 16.51 13.9 1 1
## 347 22.98 5.0 1 1
## 348 5.33 36.2 0 0
## 349 9.43 20.5 0 0
## 350 13.65 20.7 0 0
## 351 3.81 48.5 0 0
## 352 12.43 22.9 0 0
## 353 17.93 20.5 0 0
## 354 23.98 19.3 1 0
## 355 13.44 19.3 0 0
## 356 7.53 28.2 0 0
## 357 13.61 19.3 0 0
## 358 6.90 30.1 1 1
## 359 18.14 13.8 1 1
## 360 10.59 20.6 0 0
## 361 30.81 14.4 0 0
## 362 6.36 23.1 0 0
## 363 14.09 20.4 0 0
## 364 8.20 22.0 0 0
## 365 10.19 20.8 1 1
## 366 18.06 22.5 0 0
## 367 14.33 16.8 0 1
## 368 29.05 7.2 1 1
## 369 12.60 19.2 1 1
## 370 15.37 20.4 0 0
## 371 23.29 13.4 1 1
## 372 8.43 23.4 0 0
## 373 14.10 20.8 1 1
## 374 12.50 17.6 0 0
## 375 24.56 12.3 1 1
## 376 18.71 14.9 1 1
## 377 17.11 15.1 1 1
## 378 9.51 24.8 0 0
## 379 28.28 10.5 1 1
## 380 9.50 22.0 0 0
## 381 9.38 28.1 0 0
## 382 3.92 46.7 1 1
## 383 11.97 20.0 0 0
## 384 16.35 12.7 1 1
## 385 21.78 10.2 1 1
## 386 11.48 22.7 1 1
## 387 16.29 19.9 1 1
## 388 18.07 13.6 0 0
## 389 10.53 17.5 0 0
## 390 21.46 21.7 1 1
## 391 6.72 24.2 0 0
## 392 6.92 29.9 0 0
## 393 18.13 14.1 1 1
## 394 16.20 19.4 0 0
## 395 3.73 50.0 1 1
## 396 4.50 30.1 0 0
## 397 10.40 21.7 0 0
## 398 20.31 12.1 1 1
## 399 11.45 20.6 1 1
## 400 15.02 15.6 1 1
## 401 18.13 19.1 1 1
## 402 4.69 30.5 0 0
## 403 13.34 20.6 1 1
## 404 6.78 24.1 0 0
## 405 19.69 14.1 1 1
## 406 9.04 23.6 0 0
## 407 2.87 36.4 0 0
## 408 5.77 24.7 0 0
## 409 17.16 11.7 1 1
## 410 13.00 21.7 0 0
## 411 11.50 16.2 0 0
## 412 14.15 20.0 0 0
## 413 9.52 24.5 0 0
## 414 9.08 20.6 0 0
## 415 16.47 19.5 0 0
## 416 6.07 24.8 0 0
## 417 8.16 22.9 0 0
## 418 17.09 18.7 0 0
## 419 6.43 24.3 1 1
## 420 5.04 37.2 0 0
## 421 7.79 18.6 0 0
## 422 5.50 27.0 1 1
## 423 1.73 50.0 1 1
## 424 21.02 13.6 1 1
## 425 18.35 13.1 1 1
## 426 9.22 19.6 0 0
## 427 13.28 19.6 1 1
## 428 15.12 17.0 1 1
## 429 13.44 15.0 1 1
## 430 17.73 15.2 1 1
## 431 8.05 33.0 0 0
## 432 4.08 33.3 0 0
## 433 12.92 21.2 0 1
## 434 10.13 24.7 0 0
## 435 5.39 34.9 0 0
## 436 17.28 14.8 1 1
## 437 4.56 29.8 0 0
## 438 29.97 6.3 1 1
## 439 2.88 50.0 0 0
## 440 11.69 20.2 1 1
## 441 6.27 28.6 0 0
## 442 16.42 16.4 1 1
## 443 10.42 21.8 1 1
## 444 6.62 34.6 0 0
## 445 8.81 22.6 0 0
## 446 3.56 37.3 0 0
## 447 26.40 17.2 1 1
## 448 5.03 31.1 0 0
## 449 17.79 14.9 1 1
## 450 11.66 29.8 1 1
## 451 34.77 13.8 1 1
## 452 13.83 19.6 1 1
## 453 6.47 33.4 0 0
## 454 27.38 8.5 1 1
## 455 16.30 15.6 1 1
## 456 7.22 23.9 0 0
## 457 29.55 23.7 1 0
## 458 19.15 27.1 0 1
## 459 8.88 50.0 1 1
## 460 10.88 24.0 1 1
## 461 16.94 13.5 1 1
## 462 15.17 11.7 1 1
## 463 21.52 11.0 1 1
## 464 12.03 16.1 1 1
## 465 12.34 21.2 0 0
## 466 25.68 9.7 1 1
library(caret)
## Loading required package: lattice
cm1 <- confusionMatrix(as.factor(df$scored_target), as.factor(df$target), positive="1", mode="everything") %>% print
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 222 20
## 1 15 209
##
## Accuracy : 0.9249
## 95% CI : (0.8971, 0.9471)
## No Information Rate : 0.5086
## P-Value [Acc > NIR] : <2e-16
##
## Kappa : 0.8497
## Mcnemar's Test P-Value : 0.499
##
## Sensitivity : 0.9127
## Specificity : 0.9367
## Pos Pred Value : 0.9330
## Neg Pred Value : 0.9174
## Precision : 0.9330
## Recall : 0.9127
## F1 : 0.9227
## Prevalence : 0.4914
## Detection Rate : 0.4485
## Detection Prevalence : 0.4807
## Balanced Accuracy : 0.9247
##
## 'Positive' Class : 1
##
library(pROC)
## Type 'citation("pROC")' for a citation.
##
## Attaching package: 'pROC'
## The following objects are masked from 'package:stats':
##
## cov, smooth, var
curve <- roc(df$target, df$scored_target)
plot(curve, main="pROC")

test_result2 <- predict(m3, newdata=trans_crime,type='response')
df1 <- bind_cols(trans_crime, data.frame(scored_target=test_result2))%>% mutate(scored_target=ifelse(scored_target>0.5, 1, 0)) %>% print
## zn indus chas nox rm rad tax black medv target sage
## 1 0.0 19.58 0 0.6050 7.929 5 403 369.30 50.0 1 2.190890
## 2 0.0 19.58 1 0.8710 5.403 5 403 396.90 13.4 1 1.000000
## 3 0.0 18.10 0 0.7400 6.485 24 666 386.73 15.4 1 1.000000
## 4 30.0 4.93 0 0.4280 6.393 6 300 374.71 23.7 0 9.654015
## 5 0.0 2.46 0 0.4880 7.155 3 193 394.12 37.9 0 2.966479
## 6 0.0 8.56 0 0.5200 6.781 5 384 395.58 26.5 0 5.449771
## 7 0.0 18.10 0 0.6930 5.453 24 666 396.90 5.0 1 1.000000
## 8 0.0 18.10 0 0.6930 4.519 24 666 88.27 7.0 1 1.000000
## 9 0.0 5.19 0 0.5150 6.316 5 224 389.71 22.2 0 7.930952
## 10 80.0 3.64 0 0.3920 5.876 1 315 395.18 20.9 0 9.049862
## 11 22.0 5.86 0 0.4310 6.438 7 330 377.07 24.8 0 9.596874
## 12 0.0 12.83 0 0.4370 6.286 5 398 383.23 21.4 0 7.483315
## 13 0.0 18.10 0 0.5320 7.061 24 666 395.28 25.0 1 4.898979
## 14 22.0 5.86 0 0.4310 8.259 7 330 396.90 42.8 1 9.622889
## 15 0.0 2.46 0 0.4880 6.153 3 193 387.11 29.6 0 5.674504
## 16 0.0 2.18 0 0.4580 6.430 3 222 394.12 28.7 0 6.503845
## 17 100.0 1.32 0 0.4110 6.816 5 256 392.90 31.6 0 7.778175
## 18 20.0 3.97 0 0.6470 5.560 5 264 392.40 22.8 1 6.180615
## 19 0.0 18.10 0 0.6790 5.896 24 666 7.68 8.3 1 2.366432
## 20 0.0 18.10 0 0.6710 6.545 24 666 396.90 10.9 1 1.378405
## 21 0.0 3.24 0 0.4600 6.144 4 430 368.57 19.8 0 8.294577
## 22 0.0 6.20 1 0.5070 6.726 8 307 360.20 29.0 1 5.873670
## 23 0.0 2.89 0 0.4450 7.416 2 276 396.90 33.2 0 6.204837
## 24 18.0 2.31 0 0.5380 6.575 1 296 396.90 24.0 0 5.983310
## 25 0.0 9.90 0 0.5440 6.382 4 304 395.21 23.1 1 5.813777
## 26 60.0 2.93 0 0.4010 6.604 1 265 376.70 29.1 0 9.066422
## 27 0.0 5.19 0 0.5150 5.985 5 224 396.90 19.0 0 7.456541
## 28 0.0 18.10 0 0.7000 5.390 24 666 396.90 11.5 1 1.449138
## 29 25.0 4.86 0 0.4260 6.167 4 281 390.64 22.9 0 7.368853
## 30 25.0 5.13 0 0.4530 6.456 8 284 396.90 22.2 0 5.761944
## 31 0.0 6.20 0 0.5040 5.981 8 307 378.35 24.3 1 5.735852
## 32 0.0 8.56 0 0.5200 6.474 5 384 395.24 19.8 0 1.974842
## 33 0.0 2.89 0 0.4450 7.820 2 276 393.53 43.8 0 8.006248
## 34 0.0 18.10 0 0.6790 6.380 24 666 60.72 9.5 1 2.323790
## 35 0.0 5.19 0 0.5150 6.059 5 224 396.14 20.6 0 7.981228
## 36 80.0 4.95 0 0.4110 6.630 4 245 396.90 27.9 0 8.809086
## 37 0.0 2.46 0 0.4880 7.831 3 193 392.63 50.0 0 6.884766
## 38 0.0 18.10 0 0.6140 6.185 24 666 379.70 14.6 1 2.073644
## 39 0.0 4.39 0 0.4420 5.898 3 352 364.61 17.2 0 6.978539
## 40 0.0 19.58 0 0.6050 6.402 5 403 330.04 22.3 1 2.408319
## 41 0.0 3.24 0 0.4600 5.868 4 430 382.44 19.3 0 8.671793
## 42 0.0 18.10 0 0.6710 6.649 24 666 363.02 13.9 1 2.774887
## 43 0.0 4.05 0 0.5100 5.859 5 296 393.23 22.6 0 5.683309
## 44 80.0 1.91 0 0.4130 5.663 4 334 382.80 18.2 0 8.893818
## 45 12.5 7.87 0 0.5240 6.009 5 311 396.90 18.9 0 4.254409
## 46 0.0 6.91 0 0.4480 6.030 3 233 392.74 16.6 0 3.937004
## 47 0.0 18.10 0 0.5830 6.312 24 666 388.62 21.2 1 7.007139
## 48 0.0 9.90 0 0.5440 5.782 4 304 396.90 19.8 0 5.412947
## 49 0.0 18.10 0 0.5320 6.229 24 666 395.33 19.6 1 3.209361
## 50 0.0 8.14 0 0.5380 6.674 4 307 380.23 21.0 1 3.701351
## 51 55.0 2.25 0 0.3890 6.453 1 300 394.72 22.0 0 8.312641
## 52 12.5 7.87 0 0.5240 6.004 5 311 386.71 18.9 0 3.885872
## 53 0.0 5.96 0 0.4990 5.933 5 279 396.90 18.9 0 5.727128
## 54 0.0 1.89 0 0.5180 6.540 1 422 389.96 16.5 0 6.426508
## 55 0.0 21.89 0 0.6240 5.693 4 437 392.11 16.2 1 2.236068
## 56 0.0 10.59 1 0.4890 5.344 4 277 396.90 20.0 1 1.000000
## 57 20.0 3.33 0 0.4429 7.820 5 216 387.31 45.4 0 6.041523
## 58 20.0 3.33 1 0.4429 7.645 5 216 377.07 46.0 0 7.162402
## 59 0.0 7.07 0 0.4690 6.421 2 242 396.90 21.6 0 4.701064
## 60 0.0 18.10 0 0.7000 5.000 24 666 396.90 7.4 1 3.391165
## 61 0.0 19.58 0 0.6050 5.877 5 403 227.61 23.8 1 4.669047
## 62 0.0 9.90 0 0.5440 4.973 4 304 350.45 16.1 1 7.949843
## 63 0.0 18.10 0 0.7400 6.459 24 666 43.06 11.8 1 2.489980
## 64 45.0 3.44 0 0.4370 6.782 5 398 393.87 32.0 0 7.739509
## 65 35.0 6.06 0 0.4379 5.706 1 304 394.02 17.1 0 8.520563
## 66 0.0 8.14 0 0.5380 5.949 4 307 396.90 20.4 1 6.260990
## 67 0.0 27.74 0 0.6090 5.414 4 711 344.05 7.0 0 1.643168
## 68 0.0 18.10 0 0.7180 6.411 24 666 318.75 16.7 1 1.000000
## 69 0.0 9.69 0 0.5850 5.390 6 391 396.90 19.7 1 5.300943
## 70 0.0 6.20 1 0.5070 6.631 8 307 388.45 25.1 1 4.949747
## 71 0.0 18.10 0 0.6310 6.216 24 666 366.15 50.0 1 1.000000
## 72 0.0 8.56 0 0.5200 6.167 5 384 392.69 20.1 0 3.316625
## 73 0.0 19.58 0 0.6050 5.875 5 403 292.29 17.4 1 2.529822
## 74 0.0 13.89 0 0.5500 6.642 5 276 392.78 28.7 0 3.987480
## 75 0.0 18.10 0 0.6140 5.304 24 666 349.48 12.0 1 1.923538
## 76 0.0 10.81 0 0.4130 6.245 4 305 377.17 23.4 0 9.736529
## 77 0.0 19.58 0 0.8710 5.597 5 403 351.85 15.4 1 2.469818
## 78 0.0 13.89 1 0.5500 5.888 5 276 392.80 23.3 0 6.708204
## 79 0.0 2.18 0 0.4580 6.998 3 222 394.63 33.4 0 7.429670
## 80 0.0 7.38 0 0.4930 6.376 5 287 396.90 23.1 0 6.833740
## 81 0.0 10.01 0 0.5470 5.913 6 432 394.95 18.8 0 2.846050
## 82 0.0 18.10 0 0.5320 6.242 24 666 396.90 23.0 1 6.024948
## 83 0.0 18.10 0 0.6930 6.471 24 666 391.98 13.1 1 1.483240
## 84 80.0 4.95 0 0.4110 6.861 4 245 396.90 28.5 0 8.549854
## 85 20.0 3.97 0 0.5750 8.297 5 264 384.54 50.0 1 5.830952
## 86 30.0 4.93 0 0.4280 6.481 6 300 379.41 23.7 0 9.082951
## 87 0.0 19.58 0 0.6050 6.943 5 403 363.43 41.3 1 1.897367
## 88 0.0 18.10 0 0.6710 6.794 24 666 396.90 13.3 1 1.483240
## 89 0.0 10.01 0 0.5470 6.176 6 432 393.30 21.2 0 5.338539
## 90 21.0 5.64 0 0.4390 5.963 4 243 395.56 19.7 0 7.436397
## 91 25.0 4.86 0 0.4260 6.727 4 281 396.90 28.0 0 8.215838
## 92 70.0 2.24 0 0.4000 7.041 5 358 371.58 29.0 0 9.539392
## 93 0.0 18.10 0 0.6790 6.782 24 666 21.57 7.5 1 3.193744
## 94 0.0 7.38 0 0.4930 6.083 5 287 396.90 22.2 0 7.569676
## 95 45.0 3.44 0 0.4370 6.951 5 398 377.68 37.0 0 8.916277
## 96 0.0 18.10 0 0.6140 6.229 24 666 383.32 21.4 1 3.605551
## 97 40.0 1.25 0 0.4290 6.490 1 335 396.90 22.9 0 7.523297
## 98 0.0 18.10 0 0.5970 4.628 24 666 28.79 17.9 1 1.000000
## 99 0.0 18.10 0 0.7400 6.461 24 666 27.49 9.6 1 2.774887
## 100 0.0 5.19 0 0.5150 6.037 5 224 396.90 21.1 0 8.154753
## 101 0.0 8.14 0 0.5380 5.713 4 307 360.17 12.7 1 2.626785
## 102 0.0 10.59 0 0.4890 6.326 4 277 394.87 24.4 0 6.964194
## 103 0.0 19.58 0 0.8710 5.709 5 403 261.95 19.4 1 1.581139
## 104 75.0 4.00 0 0.4100 5.888 3 469 396.90 18.9 0 7.307530
## 105 0.0 18.10 0 0.5970 5.155 24 666 210.97 16.3 1 1.000000
## 106 0.0 18.10 0 0.7700 6.251 24 666 350.65 19.9 1 3.146427
## 107 0.0 11.93 0 0.5730 6.794 1 273 393.45 22.0 0 3.420526
## 108 55.0 3.78 0 0.4840 6.874 5 370 387.97 31.2 0 8.538150
## 109 0.0 21.89 0 0.6240 6.454 4 437 394.08 17.1 1 1.612452
## 110 0.0 3.24 0 0.4600 6.333 4 430 375.21 22.6 0 9.154234
## 111 0.0 6.20 0 0.5040 8.725 8 307 382.00 50.0 1 4.242641
## 112 25.0 5.13 0 0.4530 6.145 8 284 390.68 23.3 0 8.473488
## 113 0.0 5.19 0 0.5150 5.869 5 224 396.90 19.5 0 7.395945
## 114 52.5 5.32 0 0.4050 6.209 6 293 396.90 23.2 0 8.348653
## 115 0.0 6.91 0 0.4480 5.682 3 233 396.90 19.3 0 8.197561
## 116 82.5 2.03 0 0.4150 6.162 2 348 393.77 24.1 0 7.912016
## 117 0.0 18.10 0 0.6550 5.952 24 666 22.01 19.0 1 4.037326
## 118 0.0 9.90 0 0.5440 5.972 4 304 396.24 20.3 1 4.929503
## 119 0.0 21.89 0 0.6240 5.757 4 437 262.76 15.6 1 1.612452
## 120 0.0 6.20 0 0.5070 6.618 8 307 396.90 30.1 1 4.494441
## 121 0.0 8.14 0 0.5380 5.990 4 307 386.75 17.5 1 4.393177
## 122 0.0 6.91 0 0.4480 6.169 3 233 383.37 25.3 0 9.715966
## 123 0.0 6.20 0 0.5040 7.412 8 307 376.14 31.7 1 4.909175
## 124 0.0 18.10 0 0.6590 5.608 24 666 332.09 27.9 1 1.000000
## 125 20.0 3.97 0 0.6470 8.398 5 264 386.86 48.8 1 3.082207
## 126 0.0 10.01 0 0.5470 6.715 6 432 395.59 22.8 0 4.404543
## 127 0.0 18.10 0 0.6680 4.138 24 666 396.90 13.8 1 1.000000
## 128 0.0 5.19 0 0.5150 5.968 5 224 396.90 18.7 0 6.519202
## 129 0.0 8.56 0 0.5200 5.836 5 384 395.67 19.5 0 3.016621
## 130 0.0 13.92 0 0.4370 6.549 4 289 392.85 27.1 0 7.071068
## 131 0.0 18.10 0 0.6710 6.968 24 666 396.90 10.4 1 3.016621
## 132 0.0 18.10 1 0.7700 5.803 24 666 353.04 16.8 1 3.464102
## 133 25.0 4.86 0 0.4260 6.302 4 281 396.90 24.8 0 8.294577
## 134 0.0 18.10 0 0.5800 5.713 24 666 396.90 20.1 1 6.655825
## 135 90.0 1.21 1 0.4010 7.923 1 198 395.52 50.0 0 8.729261
## 136 0.0 2.89 0 0.4450 6.625 2 276 357.98 28.4 0 6.572671
## 137 12.5 7.87 0 0.5240 5.631 5 311 386.63 16.5 0 1.000000
## 138 0.0 8.14 0 0.5380 5.935 4 307 386.85 23.1 1 8.467585
## 139 0.0 21.89 0 0.6240 6.174 4 437 388.08 14.0 1 2.720294
## 140 30.0 4.93 0 0.4280 6.606 6 300 383.78 23.3 0 7.668116
## 141 0.0 6.91 0 0.4480 6.069 3 233 389.39 21.2 0 7.810250
## 142 0.0 5.96 0 0.4990 5.841 5 279 377.56 20.0 0 6.292853
## 143 0.0 19.58 1 0.6050 8.375 5 403 388.45 50.0 1 2.664583
## 144 0.0 21.89 0 0.6240 6.335 4 437 394.67 18.1 1 1.673320
## 145 0.0 9.69 0 0.5850 5.569 6 391 395.77 17.5 0 5.244044
## 146 0.0 6.20 0 0.5040 8.266 8 307 385.05 44.8 1 4.764452
## 147 0.0 21.89 0 0.6240 5.019 4 437 396.90 14.4 1 1.000000
## 148 0.0 6.20 0 0.5040 7.163 8 307 372.08 31.6 1 4.593474
## 149 0.0 18.10 0 0.7000 5.277 24 666 396.90 7.2 1 1.702939
## 150 12.5 6.07 0 0.4090 5.885 4 345 396.90 20.9 0 8.246211
## 151 0.0 18.10 0 0.7400 6.629 24 666 109.85 13.4 1 2.529822
## 152 34.0 6.09 0 0.4330 6.495 7 329 383.61 26.4 0 9.088454
## 153 0.0 10.59 1 0.4890 5.807 4 277 390.94 22.4 0 6.870226
## 154 0.0 27.74 0 0.6090 5.093 4 711 318.43 8.1 0 1.732051
## 155 0.0 19.58 0 0.6050 6.319 5 403 297.09 23.8 1 2.213594
## 156 40.0 6.41 1 0.4470 6.758 4 254 396.90 32.4 0 8.252272
## 157 0.0 18.10 0 0.7180 6.824 24 666 48.45 8.4 1 4.949747
## 158 82.5 2.03 0 0.4150 7.610 2 348 395.38 42.3 0 9.235800
## 159 0.0 8.56 0 0.5200 6.405 5 384 70.80 18.6 0 3.949684
## 160 0.0 19.58 1 0.6050 7.802 5 403 389.61 50.0 1 1.673320
## 161 0.0 18.10 0 0.5840 6.162 24 666 302.76 13.3 1 1.897367
## 162 0.0 6.20 0 0.5040 8.040 8 307 387.38 37.6 1 3.807887
## 163 20.0 3.33 0 0.4429 6.968 5 216 392.23 35.4 0 7.987490
## 164 80.0 3.37 0 0.3980 5.787 4 337 396.90 19.4 0 8.360622
## 165 0.0 4.05 0 0.5100 5.572 5 296 396.90 23.1 0 3.535534
## 166 22.0 5.86 0 0.4310 6.718 7 330 393.74 26.2 0 9.137833
## 167 52.5 5.32 0 0.4050 6.315 6 293 396.90 22.3 0 7.443118
## 168 0.0 18.10 0 0.6930 5.747 24 666 393.10 8.5 1 1.449138
## 169 0.0 18.10 0 0.6790 5.304 24 666 127.36 10.4 1 3.449638
## 170 0.0 18.10 1 0.7700 6.395 24 666 391.34 21.7 1 3.162278
## 171 75.0 2.95 0 0.4280 6.595 3 252 395.63 30.8 0 8.899438
## 172 0.0 19.58 0 0.8710 5.272 5 403 88.63 13.1 1 2.645751
## 173 0.0 8.14 0 0.5380 5.834 4 307 395.62 19.9 1 6.670832
## 174 28.0 15.04 0 0.4640 6.211 4 270 396.33 25.0 0 8.491172
## 175 20.0 3.97 0 0.6470 7.327 5 264 393.42 31.0 1 2.549510
## 176 0.0 18.10 0 0.5840 5.837 24 666 24.65 10.2 1 6.426508
## 177 0.0 18.10 0 0.7180 4.963 24 666 316.03 21.9 1 3.098387
## 178 0.0 12.83 0 0.4370 5.874 5 398 396.06 20.3 0 8.024961
## 179 0.0 18.10 0 0.7000 4.368 24 666 285.83 8.8 1 3.130495
## 180 20.0 3.97 0 0.6470 7.014 5 264 384.07 30.7 1 4.049691
## 181 0.0 3.41 0 0.4890 7.079 2 270 396.06 28.7 0 6.156298
## 182 30.0 4.93 0 0.4280 6.358 6 300 372.75 22.2 0 6.935416
## 183 0.0 18.10 0 0.7000 6.051 24 666 378.38 23.2 1 4.301163
## 184 90.0 1.22 0 0.4030 7.249 5 226 395.93 35.4 0 8.893818
## 185 0.0 2.46 0 0.4880 5.604 3 193 391.00 26.4 0 3.346640
## 186 0.0 8.56 0 0.5200 6.727 5 384 394.76 27.5 0 4.593474
## 187 90.0 3.75 0 0.3940 7.454 3 244 386.34 44.0 0 8.173127
## 188 0.0 18.10 0 0.7130 6.297 24 666 385.09 16.1 1 3.033150
## 189 0.0 18.10 1 0.7180 8.780 24 666 354.55 21.9 1 4.254409
## 190 0.0 18.10 0 0.5320 6.750 24 666 393.07 23.7 1 5.108816
## 191 55.0 3.78 0 0.4840 6.696 5 370 396.90 23.9 0 6.678323
## 192 0.0 7.38 0 0.4930 6.431 5 287 393.68 24.6 0 9.289779
## 193 20.0 6.96 0 0.4640 6.240 3 223 396.90 25.2 0 9.203260
## 194 0.0 18.10 0 0.7400 6.152 24 666 9.32 8.7 1 1.000000
## 195 0.0 19.58 1 0.8710 5.012 5 403 343.28 15.3 1 3.605551
## 196 0.0 6.91 0 0.4480 6.211 3 233 394.46 24.7 0 9.721111
## 197 0.0 11.93 0 0.5730 6.593 1 273 391.99 22.4 0 5.648008
## 198 0.0 18.10 0 0.7400 6.251 24 666 388.52 12.6 1 2.097618
## 199 0.0 18.10 0 0.5970 6.657 24 666 35.05 17.2 1 1.000000
## 200 20.0 3.97 0 0.6470 7.206 5 264 387.89 36.5 1 3.065942
## 201 80.0 3.37 0 0.3980 6.290 4 337 396.90 23.5 0 9.121403
## 202 0.0 19.58 0 0.8710 5.186 5 403 356.99 17.8 1 2.683282
## 203 0.0 18.10 0 0.6790 5.957 24 666 16.45 8.8 1 1.000000
## 204 0.0 21.89 0 0.6240 6.151 4 437 396.90 17.8 1 1.760682
## 205 25.0 5.13 0 0.4530 6.762 8 284 395.58 25.0 0 7.589466
## 206 0.0 8.14 0 0.5380 5.813 4 307 394.54 14.5 1 1.000000
## 207 70.0 2.24 0 0.4000 6.345 5 358 368.24 22.5 0 8.994443
## 208 20.0 6.96 1 0.4640 7.691 3 223 390.77 35.2 0 7.014271
## 209 22.0 5.86 0 0.4310 6.226 7 330 376.14 20.5 0 4.669047
## 210 0.0 13.89 1 0.5500 5.951 5 276 396.90 21.5 0 2.683282
## 211 0.0 18.10 0 0.6710 6.380 24 666 396.90 13.1 1 2.190890
## 212 0.0 9.69 0 0.5850 5.707 6 391 396.90 21.8 0 6.855655
## 213 0.0 21.89 0 0.6240 5.942 4 437 378.25 17.4 1 2.738613
## 214 0.0 25.65 0 0.5810 5.879 2 188 379.38 18.8 0 2.280351
## 215 0.0 18.10 0 0.7000 4.880 24 666 372.92 10.2 1 1.000000
## 216 0.0 5.19 0 0.5150 6.310 5 224 389.40 20.7 0 7.905694
## 217 0.0 18.10 0 0.5840 6.003 24 666 331.29 19.1 1 2.549510
## 218 20.0 3.97 0 0.5750 7.470 5 264 390.30 43.5 1 6.957011
## 219 0.0 18.10 0 0.6140 6.484 24 666 396.21 16.7 1 2.720294
## 220 12.5 6.07 0 0.4090 5.878 4 345 396.21 22.0 0 8.921883
## 221 20.0 3.97 0 0.6470 7.333 5 264 383.29 36.0 1 1.000000
## 222 0.0 9.90 0 0.5440 6.023 4 304 396.30 19.4 1 3.255764
## 223 35.0 1.52 0 0.4420 7.241 1 284 394.74 32.7 0 7.190271
## 224 20.0 3.97 0 0.6470 8.704 5 264 389.70 50.0 1 3.754997
## 225 0.0 6.20 0 0.5070 7.358 8 307 390.07 31.5 1 5.422177
## 226 0.0 13.92 0 0.4370 5.790 4 289 396.90 20.3 0 6.557439
## 227 0.0 27.74 0 0.6090 5.454 4 711 395.09 15.2 0 2.880972
## 228 0.0 6.20 0 0.5070 8.337 8 307 385.91 41.7 1 5.263079
## 229 0.0 8.14 0 0.5380 6.072 4 307 376.73 14.5 1 1.000000
## 230 0.0 18.10 0 0.7130 6.317 24 666 396.90 19.5 1 4.242641
## 231 0.0 18.10 0 0.6550 5.759 24 666 334.40 19.9 1 7.266361
## 232 0.0 18.10 0 0.7130 7.393 24 666 375.87 17.8 1 1.303840
## 233 0.0 7.38 0 0.4930 5.708 5 287 391.13 18.5 1 5.167204
## 234 0.0 18.10 0 0.5830 6.114 24 666 392.68 19.1 1 4.604346
## 235 0.0 13.89 1 0.5500 6.373 5 276 393.74 23.0 0 2.932576
## 236 95.0 1.47 0 0.4030 7.135 3 402 384.30 32.9 0 9.332738
## 237 80.0 1.91 0 0.4130 5.936 4 334 376.04 20.6 0 9.027735
## 238 34.0 6.09 0 0.4330 6.982 7 329 390.43 33.1 0 9.126883
## 239 0.0 4.05 0 0.5100 6.020 5 296 393.23 23.2 0 7.334848
## 240 0.0 21.89 0 0.6240 5.857 4 437 392.04 13.3 0 1.673320
## 241 0.0 18.10 0 0.7400 6.406 24 666 385.96 17.1 1 1.949359
## 242 0.0 9.90 0 0.5440 5.914 4 304 390.70 17.8 1 4.219005
## 243 0.0 19.58 0 0.8710 5.628 5 403 169.27 15.6 1 1.000000
## 244 0.0 18.10 0 0.7130 6.436 24 666 100.19 14.3 1 3.619392
## 245 40.0 6.41 0 0.4470 6.482 4 254 396.90 29.1 0 8.300602
## 246 0.0 25.65 0 0.5810 5.870 2 188 389.15 22.0 0 5.594640
## 247 0.0 18.10 0 0.7180 6.006 24 666 319.98 14.2 1 2.387467
## 248 0.0 19.58 0 0.8710 4.926 5 403 391.71 14.6 1 2.302173
## 249 0.0 8.56 0 0.5200 6.229 5 384 391.23 19.4 1 3.130495
## 250 0.0 10.81 0 0.4130 5.961 4 305 376.94 21.7 0 9.137833
## 251 20.0 3.33 0 0.4429 6.812 5 216 396.90 35.1 0 8.294577
## 252 0.0 2.46 0 0.4880 6.563 3 193 396.90 32.5 0 2.323790
## 253 0.0 18.10 0 0.7700 6.112 24 666 390.74 22.6 1 4.438468
## 254 95.0 1.47 0 0.4030 6.975 3 402 396.90 34.9 0 9.257429
## 255 20.0 3.97 0 0.6470 7.203 5 264 392.80 33.8 1 4.381780
## 256 0.0 18.10 0 0.6930 5.987 24 666 396.90 5.6 1 1.000000
## 257 0.0 25.65 0 0.5810 6.004 2 188 377.67 20.3 0 4.110961
## 258 0.0 2.89 0 0.4450 8.069 2 276 396.90 38.7 0 5.000000
## 259 12.5 6.07 0 0.4090 5.594 4 345 396.90 17.4 0 8.012490
## 260 0.0 19.58 0 0.8710 4.903 5 403 396.90 11.8 1 1.788854
## 261 40.0 6.41 1 0.4470 6.826 4 254 393.45 33.1 0 8.567380
## 262 22.0 5.86 0 0.4310 6.487 7 330 396.28 24.4 0 9.380832
## 263 0.0 9.69 0 0.5850 5.926 6 391 396.90 24.5 1 7.641989
## 264 0.0 10.01 0 0.5470 5.928 6 432 344.91 18.3 0 3.577709
## 265 0.0 19.58 0 0.8710 6.130 5 403 172.91 13.8 1 1.000000
## 266 0.0 3.41 0 0.4890 7.007 2 270 396.90 23.6 0 3.834058
## 267 0.0 19.58 0 0.8710 6.122 5 403 372.80 21.5 1 1.923538
## 268 0.0 19.58 0 0.8710 5.468 5 403 396.90 15.6 1 1.000000
## 269 0.0 18.10 0 0.7700 6.398 24 666 374.56 25.0 1 3.605551
## 270 0.0 11.93 0 0.5730 6.030 1 273 396.90 11.9 0 4.494441
## 271 0.0 18.10 0 0.7130 6.417 24 666 304.21 13.0 1 1.643168
## 272 0.0 18.10 0 0.6590 4.138 24 666 370.22 11.9 1 1.000000
## 273 0.0 21.89 0 0.6240 5.822 4 437 388.69 18.4 1 2.366432
## 274 0.0 4.05 0 0.5100 6.546 5 296 390.96 29.4 0 8.240146
## 275 0.0 25.65 0 0.5810 5.986 2 188 385.02 21.4 0 3.549648
## 276 0.0 18.10 0 0.7130 6.513 24 666 393.82 20.2 1 3.331666
## 277 0.0 18.10 0 0.7130 5.976 24 666 10.48 12.7 1 3.619392
## 278 0.0 8.14 0 0.5380 5.813 4 307 376.88 16.6 1 3.271085
## 279 0.0 18.10 0 0.6790 6.202 24 666 18.82 10.9 1 4.722288
## 280 22.0 5.86 0 0.4310 6.108 7 330 390.18 24.3 1 8.130191
## 281 60.0 1.69 0 0.4110 6.579 4 411 370.78 24.1 0 8.068457
## 282 12.5 7.87 0 0.5240 5.889 5 311 390.50 21.7 0 7.874008
## 283 0.0 21.89 0 0.6240 6.326 4 437 396.90 19.6 1 1.816590
## 284 0.0 18.10 0 0.7130 6.301 24 666 272.21 14.9 1 4.159327
## 285 0.0 10.81 0 0.4130 6.065 4 305 390.91 22.8 0 9.654015
## 286 0.0 18.10 0 0.5970 5.757 24 666 2.60 15.0 1 1.000000
## 287 0.0 9.90 0 0.5440 6.266 4 304 393.39 21.6 1 4.266146
## 288 0.0 10.01 0 0.5470 6.254 6 432 388.74 18.5 0 4.098780
## 289 0.0 18.10 0 0.7000 5.536 24 666 396.90 11.3 1 1.000000
## 290 0.0 18.10 0 0.6930 6.405 24 666 396.90 12.5 1 2.236068
## 291 0.0 19.58 0 0.6050 5.854 5 403 395.11 22.7 1 3.033150
## 292 0.0 8.14 0 0.5380 5.727 4 307 390.95 18.2 1 5.612486
## 293 0.0 6.20 1 0.5070 6.951 8 307 391.70 26.7 1 3.535534
## 294 0.0 4.49 0 0.4490 6.015 3 247 395.99 22.5 0 7.476630
## 295 0.0 27.74 0 0.6090 5.983 4 711 396.90 20.1 0 4.183300
## 296 0.0 18.10 1 0.7700 6.212 24 666 377.73 17.8 1 1.897367
## 297 0.0 7.38 0 0.4930 6.041 5 287 396.90 20.4 1 7.148426
## 298 0.0 18.10 0 0.6310 4.970 24 666 375.52 50.0 1 1.000000
## 299 40.0 6.41 1 0.4470 7.267 4 254 389.25 33.2 0 7.211103
## 300 0.0 6.91 0 0.4480 6.770 3 233 385.41 26.6 0 9.904544
## 301 40.0 6.41 0 0.4470 6.854 4 254 396.90 32.0 0 7.628892
## 302 0.0 10.59 0 0.4890 6.182 4 277 393.63 25.0 0 7.655064
## 303 0.0 10.59 1 0.4890 6.064 4 277 381.32 24.4 0 6.473021
## 304 0.0 9.69 0 0.5850 5.670 6 391 393.29 23.1 0 8.497058
## 305 0.0 9.90 0 0.5440 6.635 4 304 396.90 22.8 1 4.301163
## 306 33.0 2.18 0 0.4720 7.236 7 222 393.68 36.1 0 7.739509
## 307 0.0 21.89 0 0.6240 6.431 4 437 396.90 18.0 1 1.483240
## 308 0.0 18.10 0 0.7130 6.081 24 666 396.90 20.0 1 4.074310
## 309 30.0 4.93 0 0.4280 6.897 6 300 391.25 22.0 0 6.833740
## 310 20.0 6.96 0 0.4640 6.538 3 223 394.96 24.4 0 6.503845
## 311 0.0 10.59 0 0.4890 5.891 4 277 396.90 22.6 0 8.871302
## 312 0.0 18.10 0 0.6930 6.193 24 666 396.90 13.8 1 2.898275
## 313 0.0 4.05 0 0.5100 6.315 5 296 395.60 24.6 0 5.253570
## 314 0.0 4.49 0 0.4490 6.389 3 247 396.90 23.9 0 7.280110
## 315 0.0 21.89 0 0.6240 6.372 4 437 385.76 23.0 1 1.760682
## 316 0.0 10.01 0 0.5470 6.021 6 432 394.51 19.2 0 4.289522
## 317 40.0 1.25 0 0.4290 6.939 1 335 389.85 26.6 0 8.154753
## 318 0.0 2.46 0 0.4880 6.144 3 193 396.90 36.2 0 6.228965
## 319 0.0 7.38 0 0.4930 6.426 5 287 396.90 23.8 0 6.978539
## 320 0.0 18.10 0 0.6930 6.343 24 666 396.90 7.2 1 1.000000
## 321 0.0 6.20 1 0.5070 6.879 8 307 390.39 27.5 1 4.827007
## 322 20.0 3.97 0 0.6470 7.520 5 264 388.37 43.1 1 3.405877
## 323 0.0 18.10 0 0.5970 6.852 24 666 179.36 27.5 1 1.000000
## 324 30.0 4.93 0 0.4280 6.095 6 300 394.62 20.1 0 5.991661
## 325 0.0 9.90 0 0.5440 6.113 4 304 396.23 21.0 1 6.496153
## 326 0.0 13.92 0 0.4370 6.127 4 289 396.90 23.9 0 9.088454
## 327 75.0 2.95 0 0.4280 7.024 3 252 395.62 34.9 0 9.230385
## 328 80.0 1.52 0 0.4040 7.107 2 329 354.31 30.3 0 8.024961
## 329 0.0 8.14 0 0.5380 6.096 4 307 248.31 13.5 1 2.024846
## 330 22.0 5.86 0 0.4310 5.605 7 330 389.13 18.5 0 5.549775
## 331 0.0 18.10 0 0.7130 6.749 24 666 0.32 13.4 1 2.898275
## 332 12.5 7.87 0 0.5240 6.377 5 311 392.52 15.0 0 2.588436
## 333 0.0 8.14 0 0.5380 6.142 4 307 396.90 15.2 1 3.049590
## 334 35.0 6.06 0 0.4379 6.031 1 304 362.25 19.4 0 8.814760
## 335 0.0 18.10 0 0.6930 5.349 24 666 396.90 8.3 1 2.236068
## 336 0.0 18.10 0 0.5800 6.437 24 666 393.37 23.2 1 5.099020
## 337 80.0 3.64 0 0.3920 6.108 1 315 392.89 21.9 0 8.306624
## 338 20.0 6.96 0 0.4640 5.856 3 223 388.65 21.1 1 7.674634
## 339 0.0 12.83 0 0.4370 6.140 5 398 386.96 20.8 0 7.429670
## 340 0.0 9.90 0 0.5440 6.567 4 304 395.69 23.8 1 3.701351
## 341 0.0 19.58 0 0.8710 6.510 5 403 364.31 23.3 1 1.000000
## 342 0.0 2.46 0 0.4880 7.765 3 193 395.56 39.8 0 4.207137
## 343 80.0 0.46 0 0.4220 7.875 4 255 394.23 50.0 0 8.306624
## 344 0.0 18.10 0 0.6310 3.863 24 666 131.42 23.1 1 1.000000
## 345 21.0 5.64 0 0.4390 6.511 4 243 396.90 25.0 0 8.938680
## 346 0.0 8.14 0 0.5380 5.599 4 307 303.42 13.9 1 3.911521
## 347 0.0 18.10 0 0.6930 5.683 24 666 384.97 5.0 1 1.000000
## 348 0.0 2.18 0 0.4580 7.147 3 222 396.90 36.2 0 6.841053
## 349 21.0 5.64 0 0.4390 6.115 4 243 393.97 20.5 0 6.164414
## 350 20.0 6.96 1 0.4640 5.920 3 223 391.34 20.7 0 6.284903
## 351 95.0 2.68 0 0.4161 7.853 4 224 392.78 48.5 0 8.234076
## 352 12.5 7.87 0 0.5240 6.012 5 311 395.60 22.9 0 5.865151
## 353 0.0 25.65 0 0.5810 5.961 2 188 378.09 20.5 0 2.846050
## 354 0.0 10.59 1 0.4890 5.404 4 277 395.24 19.3 1 3.521363
## 355 0.0 8.56 0 0.5200 6.137 5 384 394.47 19.3 0 3.687818
## 356 33.0 2.18 0 0.4720 6.849 7 222 396.90 28.2 0 5.540758
## 357 0.0 10.01 0 0.5470 5.731 6 432 391.50 19.3 0 5.983310
## 358 20.0 3.97 0 0.6470 6.842 5 264 391.93 30.1 1 1.000000
## 359 0.0 18.10 0 0.5840 5.427 24 666 352.58 13.8 1 2.366432
## 360 28.0 15.04 0 0.4640 6.249 4 270 396.90 20.6 0 4.868265
## 361 0.0 6.91 0 0.4480 5.399 3 233 396.90 14.4 0 2.387467
## 362 85.0 4.15 0 0.4290 6.516 4 351 392.43 23.1 0 8.561542
## 363 0.0 8.56 0 0.5200 6.127 5 384 387.69 20.4 0 3.974921
## 364 0.0 3.41 0 0.4890 6.405 2 270 393.55 22.0 0 5.205766
## 365 0.0 18.10 0 0.7700 5.362 24 666 380.79 20.8 1 2.190890
## 366 0.0 10.59 0 0.4890 5.783 4 277 389.43 22.5 0 5.319774
## 367 0.0 9.69 0 0.5850 6.027 6 391 396.90 16.8 0 4.615192
## 368 0.0 18.10 0 0.6790 6.434 24 666 27.25 7.2 1 1.000000
## 369 0.0 21.89 0 0.6240 6.458 4 437 395.04 19.2 1 1.449138
## 370 0.0 10.01 0 0.5470 5.872 6 432 338.63 20.4 0 5.282045
## 371 0.0 18.10 0 0.6140 6.103 24 666 2.52 13.4 1 3.987480
## 372 21.0 5.64 0 0.4390 5.998 4 243 396.90 23.4 0 8.921883
## 373 0.0 18.10 0 0.6140 5.648 24 666 291.55 20.8 1 3.660601
## 374 22.0 5.86 0 0.4310 5.593 7 330 372.49 17.6 0 4.949747
## 375 0.0 18.10 0 0.7000 5.520 24 666 396.90 12.3 1 1.000000
## 376 0.0 18.10 0 0.7130 6.728 24 666 6.68 14.9 1 2.626785
## 377 0.0 18.10 0 0.7000 5.713 24 666 394.43 15.1 1 2.000000
## 378 52.5 5.32 0 0.4050 6.565 6 293 371.72 24.8 0 8.837420
## 379 0.0 18.10 0 0.7000 4.652 24 666 396.90 10.5 1 1.000000
## 380 34.0 6.09 0 0.4330 6.590 7 329 395.75 22.0 0 7.784600
## 381 0.0 10.59 0 0.4890 6.375 4 277 385.81 28.1 0 8.288546
## 382 0.0 6.20 0 0.5040 7.686 8 307 377.51 46.7 1 9.165151
## 383 0.0 12.83 0 0.4370 6.279 5 398 373.66 20.0 0 5.147815
## 384 0.0 18.10 0 0.6930 5.887 24 666 396.90 12.7 1 2.509980
## 385 0.0 18.10 0 0.6710 6.223 24 666 393.74 10.2 1 1.000000
## 386 0.0 18.10 1 0.7700 6.127 24 666 395.43 22.7 1 4.195235
## 387 0.0 18.10 0 0.5800 6.167 24 666 396.90 19.9 1 4.123106
## 388 0.0 27.74 0 0.6090 5.983 4 711 390.11 13.6 0 1.483240
## 389 0.0 4.39 0 0.4420 6.014 3 352 385.64 17.5 0 7.245688
## 390 0.0 6.20 1 0.5070 6.164 8 307 395.24 21.7 1 3.114482
## 391 0.0 10.81 0 0.4130 6.417 4 305 383.73 24.2 0 9.715966
## 392 0.0 4.05 0 0.5100 6.860 5 296 391.27 29.9 0 5.157519
## 393 0.0 18.10 0 0.7130 6.185 24 666 396.90 14.1 1 1.516575
## 394 0.0 6.91 0 0.4480 5.602 3 233 396.90 19.4 0 6.244998
## 395 0.0 18.10 1 0.6310 6.683 24 666 375.33 50.0 1 2.049390
## 396 90.0 2.02 0 0.4100 6.728 5 187 384.46 30.1 0 8.056054
## 397 0.0 13.92 0 0.4370 6.009 4 289 396.90 21.7 0 7.661593
## 398 0.0 18.10 0 0.6930 6.404 24 666 376.11 12.1 1 1.000000
## 399 0.0 18.10 0 0.5830 5.905 24 666 388.22 20.6 1 6.913754
## 400 0.0 19.58 1 0.8710 6.152 5 403 88.01 15.6 1 4.289522
## 401 0.0 18.10 0 0.5800 5.926 24 666 368.74 19.1 1 5.477226
## 402 45.0 3.44 0 0.4370 6.739 5 398 389.71 30.5 0 8.378544
## 403 0.0 18.10 0 0.5830 5.871 24 666 370.73 20.6 1 7.687652
## 404 0.0 12.83 0 0.4370 6.273 5 398 394.92 24.1 0 9.746794
## 405 0.0 18.10 0 0.5840 6.833 24 666 81.33 14.1 1 2.588436
## 406 0.0 4.05 0 0.5100 6.416 5 296 395.50 23.6 0 4.110961
## 407 45.0 3.44 0 0.4370 7.178 5 398 390.49 36.4 0 8.642916
## 408 85.0 0.74 0 0.4100 6.383 2 313 396.90 24.7 0 8.080842
## 409 0.0 18.10 0 0.5840 5.565 24 666 3.65 11.7 1 5.513620
## 410 0.0 8.56 0 0.5200 6.195 5 384 393.49 21.7 0 6.826419
## 411 0.0 9.90 0 0.5440 5.705 4 304 396.42 16.2 0 4.827007
## 412 0.0 6.91 0 0.4480 5.786 3 233 396.90 20.0 0 8.228001
## 413 22.0 5.86 0 0.4310 6.433 7 330 374.71 24.5 0 7.204165
## 414 0.0 11.93 0 0.5730 6.120 1 273 396.90 20.6 0 4.929503
## 415 0.0 8.56 0 0.5200 5.851 5 384 394.05 19.5 0 2.073644
## 416 70.0 2.24 0 0.4000 6.871 5 358 390.86 24.8 0 7.321202
## 417 28.0 15.04 0 0.4640 6.442 4 270 395.01 22.9 0 6.884766
## 418 0.0 10.01 0 0.5470 6.092 6 432 396.90 18.7 0 2.366432
## 419 0.0 19.58 0 0.6050 6.066 5 403 353.89 24.3 1 1.000000
## 420 0.0 2.46 0 0.4880 6.980 3 193 396.90 37.2 0 6.526868
## 421 60.0 1.69 0 0.4110 5.884 4 411 392.33 18.6 0 9.082951
## 422 0.0 19.58 1 0.6050 6.250 5 403 338.92 27.0 1 2.898275
## 423 0.0 19.58 0 0.6050 7.489 5 403 374.43 50.0 1 3.193744
## 424 0.0 8.14 0 0.5380 5.570 4 307 376.57 13.6 1 1.702939
## 425 0.0 8.14 0 0.5380 5.701 4 307 358.77 13.1 1 2.449490
## 426 25.0 5.13 0 0.4530 5.927 8 284 396.90 19.6 0 7.334848
## 427 0.0 19.58 0 0.8710 5.404 5 403 341.60 19.6 1 1.000000
## 428 0.0 19.58 1 0.8710 6.129 5 403 321.02 17.0 1 2.236068
## 429 0.0 18.10 0 0.6710 7.313 24 666 396.90 15.0 1 1.760682
## 430 0.0 18.10 0 0.7130 6.655 24 666 355.29 15.2 1 1.673320
## 431 17.5 1.38 0 0.4161 7.104 3 216 393.24 33.0 0 6.442049
## 432 80.0 1.52 0 0.4040 7.287 2 329 396.90 33.3 0 8.179242
## 433 0.0 9.69 0 0.5850 6.019 6 391 396.90 21.2 0 5.974948
## 434 0.0 5.96 0 0.4990 5.966 5 279 393.43 24.7 0 8.414274
## 435 45.0 3.44 0 0.4370 7.185 5 398 396.90 34.9 0 7.880355
## 436 0.0 8.14 0 0.5380 6.047 4 307 306.38 14.8 1 3.492850
## 437 45.0 3.44 0 0.4370 6.556 5 398 382.84 29.8 0 8.479387
## 438 0.0 18.10 0 0.6930 5.852 24 666 338.16 6.3 1 4.816638
## 439 95.0 2.68 0 0.4161 8.034 4 224 390.55 50.0 0 8.312641
## 440 0.0 8.14 0 0.5380 5.456 4 307 288.99 20.2 1 8.024961
## 441 0.0 13.92 0 0.4370 6.678 4 289 396.90 28.6 0 8.360622
## 442 0.0 18.10 0 0.7130 6.701 24 666 255.23 16.4 1 3.316625
## 443 0.0 18.10 0 0.5320 5.762 24 666 392.92 21.8 1 7.791020
## 444 80.0 1.52 0 0.4040 7.274 2 329 392.20 34.6 0 7.918333
## 445 0.0 3.41 0 0.4890 6.417 2 270 392.18 22.6 0 5.907622
## 446 80.0 4.95 0 0.4110 7.148 4 245 396.90 37.3 0 8.561542
## 447 0.0 18.10 0 0.5970 5.617 24 666 314.64 17.2 1 1.760682
## 448 60.0 2.93 0 0.4010 6.800 1 265 393.37 31.1 0 9.544632
## 449 0.0 18.10 0 0.7400 6.341 24 666 318.01 14.9 1 2.144761
## 450 0.0 18.10 0 0.6140 6.980 24 666 374.68 29.8 1 5.779273
## 451 0.0 18.10 0 0.6680 4.906 24 666 396.90 13.8 1 1.000000
## 452 0.0 8.14 0 0.5380 5.965 4 307 392.53 19.6 1 3.435113
## 453 33.0 2.18 0 0.4720 7.420 7 222 396.90 33.4 0 5.394442
## 454 0.0 18.10 0 0.6930 5.531 24 666 329.46 8.5 1 3.949684
## 455 0.0 8.14 0 0.5380 5.924 4 307 394.33 15.6 1 2.626785
## 456 25.0 4.86 0 0.4260 6.619 4 281 395.63 23.9 0 5.531727
## 457 0.0 10.59 0 0.4890 5.412 4 277 348.93 23.7 1 9.549869
## 458 12.5 7.87 0 0.5240 6.172 5 311 396.90 27.1 0 2.213594
## 459 0.0 18.10 1 0.6680 5.875 24 666 347.88 50.0 1 3.376389
## 460 0.0 6.20 0 0.5070 6.086 8 307 376.75 24.0 1 6.284903
## 461 0.0 18.10 0 0.7130 5.936 24 666 3.50 13.5 1 4.549725
## 462 0.0 18.10 0 0.7130 6.208 24 666 100.63 11.7 1 2.449490
## 463 0.0 18.10 0 0.6790 6.193 24 666 96.73 11.0 1 4.785394
## 464 0.0 18.10 0 0.5840 6.425 24 666 97.95 16.1 1 5.118594
## 465 0.0 12.83 0 0.4370 6.232 5 398 386.40 21.2 0 6.877500
## 466 0.0 18.10 0 0.7000 5.036 24 666 396.90 9.7 1 2.000000
## lptratio ldis clstat scored_target
## 1 2.1162555 0.7158378 1.546680 1
## 2 2.1162555 0.2788431 2.993318 1
## 3 1.0296194 0.6822884 2.661361 1
## 4 1.8562980 1.9509688 1.731367 0
## 5 1.6486586 0.9934740 1.689205 0
## 6 0.7419373 1.0494571 1.972113 0
## 7 1.0296194 0.3985076 3.127470 1
## 8 1.0296194 0.5057327 3.331621 1
## 9 1.0296194 1.8653816 1.784224 1
## 10 1.8870696 2.2214076 2.099168 0
## 11 1.3609766 2.0010340 1.531198 0
## 12 1.4586150 1.5046550 2.075451 0
## 13 1.0296194 1.2268882 1.913842 1
## 14 1.3609766 2.1868038 1.524057 0
## 15 1.6486586 1.1877520 2.360344 0
## 16 1.4586150 1.8020728 1.733588 0
## 17 2.0668628 2.1192390 1.580759 0
## 18 2.3025851 0.6863743 2.186278 1
## 19 1.0296194 0.6468938 2.900040 1
## 20 1.0296194 0.4181839 2.762423 1
## 21 1.8082888 1.7704677 2.086994 0
## 22 1.7227666 1.2952476 2.004158 1
## 23 1.6094379 1.2513906 1.836102 0
## 24 2.0412203 1.4085450 1.707693 0
## 25 1.5260563 1.2620058 2.179984 0
## 26 2.0014800 1.8277056 1.636156 0
## 27 1.0296194 1.5711544 2.135599 0
## 28 1.0296194 0.5470225 2.752340 1
## 29 1.3862944 1.6865286 1.958303 0
## 30 1.1939225 1.9776164 1.888013 0
## 31 1.7227666 1.3006003 2.266950 1
## 32 0.7419373 0.8890840 2.306472 0
## 33 1.6094379 1.2513906 1.528350 0
## 34 1.0296194 0.6771194 2.887701 1
## 35 1.0296194 1.5711544 2.041628 0
## 36 1.3350011 1.6325097 1.675069 0
## 37 1.6486586 1.1629008 1.644826 0
## 38 1.0296194 0.7749576 2.622197 1
## 39 1.4350845 2.0811401 2.331268 0
## 40 2.1162555 0.8164704 2.245340 1
## 41 1.8082888 1.6514624 2.152278 0
## 42 1.0296194 0.2963197 2.853724 1
## 43 1.8562980 0.9939552 2.128265 0
## 44 0.0000000 2.3595040 2.004158 0
## 45 2.0541237 1.8288465 2.367502 0
## 46 1.6292405 1.7386048 2.659006 0
## 47 1.0296194 1.3842172 2.195307 1
## 48 1.5260563 1.3941881 2.516688 0
## 49 1.0296194 1.1311763 2.343471 1
## 50 0.6931472 1.4443274 2.288156 1
## 51 2.0412203 1.9888738 2.018986 0
## 52 2.0541237 1.8858720 2.576313 0
## 53 1.3350011 1.2120303 2.131204 0
## 54 1.9600948 1.8352818 2.052762 0
## 55 0.5877867 0.5812654 2.580825 1
## 56 1.4816045 1.3545457 2.847572 1
## 57 2.0918641 1.5464342 1.554996 0
## 58 2.0918641 1.6509445 1.443850 0
## 59 1.6486586 1.6028362 2.090814 0
## 60 1.0296194 0.4176571 3.174471 1
## 61 2.1162555 0.8862026 2.298297 1
## 62 1.5260563 0.9240208 2.329427 0
## 63 1.0296194 0.6870788 2.883698 1
## 64 2.0541237 1.3319966 1.883326 0
## 65 1.8082888 1.8932174 2.316454 0
## 66 0.6931472 1.5491570 2.021436 1
## 67 1.0647107 0.5626968 2.883297 0
## 68 1.0296194 0.6199849 2.467308 1
## 69 1.3350011 1.0291193 2.765042 1
## 70 1.7227666 1.4226263 2.120880 1
## 71 1.0296194 0.1562342 2.120139 1
## 72 0.7419373 0.8841807 2.310225 0
## 73 2.1162555 0.8862026 2.434569 1
## 74 1.8870696 1.2299621 2.131938 1
## 75 1.0296194 0.7422706 2.920505 1
## 76 1.3350011 1.6653077 1.960908 0
## 77 2.1162555 0.4224533 2.778492 1
## 78 1.8870696 1.1352977 2.381689 0
## 79 1.4586150 1.8020728 1.432570 0
## 80 1.2237754 1.5130151 1.901015 0
## 81 1.6486586 0.8558611 2.530819 0
## 82 1.0296194 1.2308679 2.206318 1
## 83 1.0296194 0.5456328 2.577317 1
## 84 1.3350011 1.6325097 1.493303 0
## 85 2.3025851 0.8844285 1.952200 1
## 86 1.8562980 1.8229189 1.852759 0
## 87 2.1162555 0.6298346 1.661897 1
## 88 1.0296194 0.3060130 2.769395 1
## 89 1.6486586 1.0043382 2.291969 0
## 90 1.8245493 1.9190820 2.378158 0
## 91 1.3862944 1.6865286 1.742416 0
## 92 2.1041342 2.0576815 1.679807 0
## 93 1.0296194 0.5985617 2.954499 1
## 94 1.2237754 1.6893391 2.338605 0
## 95 2.0541237 1.8686896 1.721301 0
## 96 1.0296194 0.6684446 2.357948 1
## 97 1.1939225 2.1738536 1.815099 0
## 98 1.0296194 0.4407679 3.251321 1
## 99 1.0296194 0.6944463 2.623166 1
## 100 1.0296194 1.7893065 2.000833 1
## 101 0.6931472 1.4429110 2.827284 1
## 102 1.4816045 1.4713016 2.221956 0
## 103 2.1162555 0.4843995 2.508769 1
## 104 0.6418539 1.9905693 2.455202 0
## 105 1.0296194 0.4633566 2.718032 1
## 106 1.0296194 0.8309507 2.420996 1
## 107 0.6931472 0.8708330 1.864340 0
## 108 1.6863990 1.8664649 1.664308 0
## 109 0.5877867 0.6150775 2.443534 1
## 110 1.8082888 1.6514624 1.943414 0
## 111 1.7227666 1.0627778 1.666711 1
## 112 1.1939225 2.0560194 1.900092 0
## 113 1.0296194 1.6546216 2.139975 1
## 114 1.8562980 1.9902277 1.925600 0
## 115 1.6292405 1.6293190 2.169411 0
## 116 2.1162555 1.8357764 1.951325 0
## 117 1.0296194 1.0548345 2.578822 1
## 118 1.5260563 1.1322082 2.152278 0
## 119 0.5877867 0.8527118 2.586817 1
## 120 1.7227666 1.1854320 1.966095 1
## 121 0.6931472 1.4487761 2.447992 1
## 122 1.6292405 1.7441261 1.797734 0
## 123 1.7227666 1.3006003 1.738013 1
## 124 1.0296194 0.2509143 2.297666 1
## 125 2.3025851 0.8278966 1.807989 1
## 126 1.6486586 0.9848835 2.165864 0
## 127 1.0296194 0.1283932 3.361090 1
## 128 1.0296194 1.5711544 2.102190 0
## 129 0.7419373 0.7934449 2.652389 0
## 130 1.9459101 1.7851376 1.947817 0
## 131 1.0296194 0.3481890 2.581826 1
## 132 1.0296194 0.6443245 2.446322 1
## 133 1.3862944 1.6865286 1.887078 0
## 134 1.0296194 1.0380481 2.452988 1
## 135 2.2407097 1.7724067 1.467447 0
## 136 1.6094379 1.2513906 1.880502 0
## 137 2.0541237 1.8053500 3.104814 1
## 138 0.6931472 1.5037662 1.873881 1
## 139 0.5877867 0.4774136 2.890895 1
## 140 1.8562980 1.8229189 1.946058 0
## 141 1.6292405 1.7441261 2.121621 0
## 142 1.3350011 1.2172542 2.251275 0
## 143 2.1162555 0.7710337 1.491807 1
## 144 0.5877867 0.7470196 2.569263 1
## 145 1.3350011 0.8754271 2.471680 1
## 146 1.7227666 1.0627778 1.605709 1
## 147 0.5877867 0.3642264 3.252582 1
## 148 1.7227666 1.1680451 1.852759 1
## 149 1.0296194 0.3549434 3.134950 1
## 150 1.4109870 1.8714944 2.063778 0
## 151 1.0296194 0.7536306 2.854952 1
## 152 1.9315214 1.7032379 2.054343 0
## 153 1.4816045 1.2954392 2.521416 0
## 154 1.0647107 0.6002641 3.096145 0
## 155 2.1162555 0.7419373 2.230699 1
## 156 1.6863990 1.4055086 1.522620 0
## 157 1.0296194 0.5844478 2.833110 1
## 158 2.1162555 1.8357764 1.459666 0
## 159 0.7419373 0.9986815 2.198760 1
## 160 2.1162555 0.7132929 1.242893 1
## 161 1.0296194 0.7911809 2.888500 1
## 162 1.7227666 1.1680451 1.462788 1
## 163 2.0918641 1.6572180 1.661897 0
## 164 1.9315214 1.8888106 2.171534 0
## 165 1.8562980 0.9540103 2.449104 0
## 166 1.3609766 2.0575154 1.871980 0
## 167 1.8562980 1.9902277 1.966095 0
## 168 1.0296194 0.4906637 2.710794 1
## 169 1.0296194 0.4992590 2.986607 1
## 170 1.0296194 0.9183686 2.367502 1
## 171 1.5475625 1.6866026 1.628651 0
## 172 2.1162555 0.5518140 2.527170 1
## 173 0.6931472 1.5037662 2.038424 1
## 174 1.5686159 1.2990739 1.838078 0
## 175 2.3025851 0.7317908 2.240702 1
## 176 1.0296194 0.6919465 2.503462 1
## 177 1.0296194 0.5609292 2.410142 1
## 178 1.4586150 1.5046550 2.087759 0
## 179 1.0296194 0.3642958 3.128833 1
## 180 2.3025851 0.7574826 2.454649 1
## 181 1.6486586 1.2280311 1.786316 0
## 182 1.8562980 1.9509688 2.238709 0
## 183 1.0296194 0.7737128 2.657119 1
## 184 1.6292405 2.1629321 1.688036 0
## 185 1.6486586 1.0945708 2.408994 0
## 186 0.7419373 1.0216592 2.111950 0
## 187 1.9600948 1.8462634 1.459666 0
## 188 1.0296194 0.8621302 2.584823 1
## 189 1.0296194 0.6443245 1.742416 1
## 190 1.0296194 1.2034827 1.978094 1
## 191 1.6863990 1.7460820 1.929189 0
## 192 1.2237754 1.6893391 1.719048 0
## 193 1.4816045 1.4881738 1.874830 0
## 194 1.0296194 0.6492998 2.979490 1
## 195 2.1162555 0.4763584 2.297035 1
## 196 1.6292405 1.7441261 1.952200 0
## 197 0.6931472 0.9076939 2.130470 0
## 198 1.0296194 0.7875479 2.542732 1
## 199 1.0296194 0.4236324 2.768525 1
## 200 2.3025851 0.6575718 2.008299 1
## 201 1.9315214 1.8888106 1.671497 0
## 202 2.1162555 0.4250063 3.048113 1
## 203 1.0296194 0.5892301 2.742182 1
## 204 0.5877867 0.5120449 2.642879 1
## 205 1.1939225 2.0770512 2.117912 0
## 206 0.6931472 1.4098156 2.708978 1
## 207 2.1041342 2.0576815 1.706549 0
## 208 1.4816045 1.4739618 1.873881 0
## 209 1.3609766 2.0863551 2.165153 0
## 210 1.8870696 1.0610143 2.616853 1
## 211 1.0296194 0.3264940 2.872026 1
## 212 1.3350011 0.8678145 2.290064 1
## 213 0.5877867 0.6764587 2.566230 1
## 214 1.3609766 0.6962922 2.600197 0
## 215 1.0296194 0.4634195 3.128492 1
## 216 1.0296194 1.8653816 1.889882 1
## 217 1.0296194 0.9322822 2.772867 1
## 218 2.3025851 1.0550087 1.467447 1
## 219 1.0296194 0.8352108 2.653336 1
## 220 1.4109870 1.8714944 2.008299 0
## 221 2.3025851 0.6390077 1.982345 1
## 222 1.5260563 1.0416891 2.271481 0
## 223 2.0149030 1.9513098 1.764104 0
## 224 2.3025851 0.5883421 1.723548 1
## 225 1.7227666 1.4226263 1.678625 1
## 226 1.9459101 1.8437192 2.511414 0
## 227 1.0647107 0.5993309 2.623650 0
## 228 1.7227666 1.3450556 1.351758 1
## 229 0.6931472 1.4291144 2.353744 1
## 230 1.0296194 1.0059120 2.409568 1
## 231 1.0296194 1.1205368 2.417579 1
## 232 1.0296194 0.8971895 2.558106 1
## 233 1.2237754 1.5520418 2.272773 0
## 234 1.0296194 1.2657920 2.465115 1
## 235 1.8870696 1.2129226 2.189760 1
## 236 1.7917595 2.0351500 1.644826 0
## 237 0.0000000 2.3595040 1.772631 0
## 238 1.9315214 1.7032379 1.693865 0
## 239 1.8562980 1.2683269 2.162305 0
## 240 0.5877867 0.5119850 2.772867 1
## 241 1.0296194 0.7251787 2.692526 1
## 242 1.5260563 1.3859443 2.636660 0
## 243 2.1162555 0.4164710 2.553513 1
## 244 1.0296194 0.8397552 2.531339 1
## 245 1.6863990 1.4207682 1.930084 0
## 246 1.3609766 0.8143466 2.431190 0
## 247 1.0296194 0.6283953 2.503994 1
## 248 2.1162555 0.3789842 3.090920 1
## 249 0.7419373 0.9341699 2.495994 0
## 250 1.3350011 1.6653077 2.145782 0
## 251 2.0918641 1.4111577 1.692702 0
## 252 1.6486586 1.0462658 1.784224 0
## 253 1.0296194 0.9199241 2.331268 1
## 254 1.7917595 2.0351500 1.658269 0
## 255 2.3025851 0.7476827 2.124579 1
## 256 1.0296194 0.4629790 2.991457 1
## 257 1.3609766 0.7872748 2.425537 0
## 258 1.6094379 1.2513906 1.614708 0
## 259 1.4109870 1.8714944 2.356748 0
## 260 2.1162555 0.2970629 3.082524 1
## 261 1.6863990 1.5816144 1.608290 0
## 262 1.3609766 2.0010340 1.806969 0
## 263 1.3350011 0.8678145 2.386381 1
## 264 1.6486586 0.9014207 2.507179 0
## 265 2.1162555 0.3500229 3.029342 1
## 266 1.6486586 1.2301375 1.765174 0
## 267 2.1162555 0.4811908 2.415867 1
## 268 2.1162555 0.3448655 2.978363 1
## 269 1.0296194 0.9235444 1.982345 1
## 270 0.6931472 0.9182887 1.989950 0
## 271 1.0296194 0.7816158 2.682836 1
## 272 1.0296194 0.1639030 2.857812 1
## 273 0.5877867 0.9041777 2.467855 1
## 274 1.8562980 1.1417676 1.746797 0
## 275 1.3609766 0.6895909 2.455755 0
## 276 1.0296194 1.0301907 2.175063 1
## 277 1.0296194 0.9480219 2.668870 1
## 278 0.6931472 1.5437254 2.455755 1
## 279 1.0296194 0.6221344 2.439620 1
## 280 1.3609766 2.0863551 2.092338 0
## 281 1.5475625 2.3712059 1.764104 0
## 282 2.0541237 1.6957807 2.504525 0
## 283 0.5877867 0.8202203 2.305845 1
## 284 1.0296194 1.0235654 2.531859 1
## 285 1.3350011 1.6653077 1.767311 0
## 286 1.0296194 0.3457151 2.162305 1
## 287 1.5260563 1.1825857 1.991632 0
## 288 1.6486586 0.8138149 2.186278 0
## 289 1.0296194 0.4576780 2.868384 1
## 290 1.0296194 0.5168872 2.685612 1
## 291 2.1162555 0.8845936 2.266301 1
## 292 0.6931472 1.3340796 2.242692 1
## 293 1.7227666 1.0514159 2.133404 1
## 294 1.5040774 1.4877673 2.342864 0
## 295 1.0647107 0.7466406 2.372250 0
## 296 1.0296194 0.7524533 2.601183 1
## 297 1.2237754 1.5520418 1.974681 0
## 298 1.0296194 0.2870569 1.482766 1
## 299 1.6863990 1.5659457 1.822154 0
## 300 1.6292405 1.7441261 1.691538 0
## 301 1.6863990 1.4509813 1.439037 0
## 302 1.4816045 1.3725503 2.115680 0
## 303 1.4816045 1.4443746 2.447436 0
## 304 1.3350011 1.0291193 2.601183 1
## 305 1.5260563 1.1992115 1.655841 0
## 306 1.5260563 1.3917793 1.906533 0
## 307 0.5877867 0.5947071 2.487403 1
## 308 1.0296194 0.9997123 2.449660 1
## 309 1.8562980 1.8462634 2.249300 0
## 310 1.4816045 1.3654537 1.977242 0
## 311 1.4816045 1.3725503 2.215184 0
## 312 1.0296194 0.5828858 2.475494 1
## 313 1.8562980 1.1992115 1.845937 0
## 314 1.5040774 1.5643150 2.126792 0
## 315 0.5877867 0.8447518 2.232038 1
## 316 1.6486586 1.0106550 2.175767 0
## 317 1.1939225 2.1738536 1.805947 0
## 318 1.6486586 0.9547034 2.114190 0
## 319 1.2237754 1.5130151 1.930979 0
## 320 1.0296194 0.4536837 2.728818 1
## 321 1.7227666 1.1854320 2.149396 1
## 322 2.3025851 0.7607124 1.936328 1
## 323 1.0296194 0.3821965 2.704428 1
## 324 1.8562980 1.8462634 2.314589 0
## 325 1.5260563 1.3867692 2.334942 0
## 326 1.9459101 1.7052389 2.047210 0
## 327 1.5475625 1.6866026 1.255707 0
## 328 2.3418058 1.9891065 2.049593 0
## 329 0.6931472 1.3243658 2.729713 1
## 330 1.3609766 2.0737881 2.642879 0
## 331 1.0296194 0.8431177 2.593277 1
## 332 2.0541237 1.8479350 2.734625 0
## 333 0.6931472 1.3805026 2.655229 1
## 334 1.8082888 1.8932174 1.985732 0
## 335 1.0296194 0.5322740 2.703972 1
## 336 1.0296194 1.0635031 2.430626 1
## 337 1.8870696 2.2214076 1.872931 0
## 338 1.4816045 1.4881738 2.351335 0
## 339 1.4586150 1.4086672 2.173653 0
## 340 1.5260563 1.2815725 2.101435 0
## 341 2.1162555 0.5686605 1.947817 1
## 342 1.6486586 1.0083228 1.962640 0
## 343 2.1517622 1.7313723 1.437426 0
## 344 1.0296194 0.4125069 2.371065 1
## 345 1.8245493 1.9190820 1.741318 0
## 346 0.6931472 1.4939373 2.546336 1
## 347 1.0296194 0.3544525 2.843042 1
## 348 1.4586150 1.8020728 1.746797 0
## 349 1.8245493 1.9190820 2.112697 0
## 350 1.4816045 1.3654537 2.389888 0
## 351 2.1162555 1.6327637 1.561858 0
## 352 2.0541237 1.7156880 2.316454 0
## 353 1.3609766 0.7356797 2.617340 0
## 354 1.4816045 1.2988283 2.883698 0
## 355 0.7419373 0.9986815 2.377569 0
## 356 1.5260563 1.1577299 1.960040 0
## 357 1.6486586 1.0149408 2.387551 0
## 358 2.3025851 0.6984829 1.903778 1
## 359 1.0296194 0.8878089 2.627518 1
## 360 1.5686159 1.2850919 2.195998 0
## 361 1.6292405 1.7698546 3.134950 0
## 362 1.6292405 2.1442105 1.852759 0
## 363 0.7419373 0.7525475 2.415296 0
## 364 1.6486586 1.1288505 2.016530 0
## 365 1.0296194 0.7436502 2.167994 1
## 366 1.4816045 1.4713016 2.623650 0
## 367 1.3350011 0.9155705 2.428932 1
## 368 1.0296194 0.6068810 3.074082 1
## 369 0.5877867 0.7507083 2.326967 1
## 370 1.6486586 0.9072500 2.486325 0
## 371 1.0296194 0.7039882 2.855770 1
## 372 1.8245493 1.9190820 2.035210 0
## 373 1.0296194 0.6684446 2.415867 1
## 374 1.3609766 2.0737881 2.320794 0
## 375 1.0296194 0.4272918 2.906762 1
## 376 1.0296194 0.9147295 2.654756 1
## 377 1.0296194 0.6557049 2.576816 1
## 378 1.8562980 1.9902277 2.118655 0
## 379 1.0296194 0.3833558 3.046677 1
## 380 1.9315214 1.7032379 2.117912 0
## 381 1.4816045 1.3725503 2.108956 0
## 382 1.7227666 1.2164250 1.576747 1
## 383 1.4586150 1.3992599 2.287519 0
## 384 1.0296194 0.5777924 2.538084 1
## 385 1.0296194 0.3264940 2.792668 1
## 386 1.0296194 1.0016240 2.255869 1
## 387 1.0296194 1.1096841 2.534975 1
## 388 1.0647107 0.6249219 2.624134 0
## 389 1.4350845 2.0811401 2.191843 0
## 390 1.7227666 1.1144856 2.778923 1
## 391 1.3350011 1.6653077 1.887078 0
## 392 1.8562980 1.0699727 1.905616 0
## 393 1.0296194 0.8160725 2.627035 1
## 394 1.6292405 1.8062703 2.530298 0
## 395 1.0296194 0.3050553 1.550849 1
## 396 1.7917595 2.4953931 1.650964 0
## 397 1.9459101 1.7052389 2.182786 0
## 398 1.0296194 0.4940863 2.728370 1
## 399 1.0296194 1.1481323 2.253903 1
## 400 2.1162555 0.5570410 2.467308 1
## 401 1.0296194 1.0676031 2.627035 1
## 402 2.0541237 1.8686896 1.673880 0
## 403 1.0296194 1.3147984 2.371657 1
## 404 1.4586150 1.4472719 1.892677 0
## 405 1.0296194 0.7363025 2.700320 1
## 406 1.8562980 0.9731624 2.083161 0
## 407 2.0541237 1.8686896 1.421109 0
## 408 1.7404662 2.2178547 1.793599 0
## 409 1.0296194 0.7244036 2.579323 1
## 410 0.7419373 1.0216592 2.351335 0
## 411 1.5260563 1.3724490 2.257179 0
## 412 1.6292405 1.6293190 2.418719 0
## 413 1.3609766 2.0575154 2.119397 0
## 414 0.6931472 0.8274595 2.086229 0
## 415 0.7419373 0.7452177 2.544278 0
## 416 2.1041342 2.0576815 1.824160 0
## 417 1.5686159 1.2990739 2.013245 0
## 418 1.6486586 0.9353087 2.575811 0
## 419 2.1162555 0.5637785 1.859532 1
## 420 1.6486586 1.0399233 1.714524 0
## 421 1.5475625 2.3712059 1.982345 0
## 422 2.1162555 0.5868974 1.765174 1
## 423 2.1162555 0.6784903 1.200463 1
## 424 0.6931472 1.3344483 2.759800 1
## 425 0.6931472 1.3316270 2.637619 1
## 426 1.1939225 1.9361484 2.096896 0
## 427 2.1162555 0.4647398 2.368096 1
## 428 2.1162555 0.5592729 2.472771 1
## 429 1.0296194 0.2748248 2.377569 1
## 430 1.0296194 0.8566256 2.607572 1
## 431 1.4816045 2.2216895 2.004158 0
## 432 2.3418058 1.9891065 1.597914 0
## 433 1.3350011 0.8792532 2.346502 1
## 434 1.3350011 1.3473716 2.163730 0
## 435 2.0541237 1.5187908 1.753327 0
## 436 0.6931472 1.4936678 2.585322 1
## 437 2.0541237 1.5187908 1.658269 0
## 438 1.0296194 0.4057317 3.106196 1
## 439 2.1162555 1.6327637 1.422757 0
## 440 0.6931472 1.3340796 2.269542 1
## 441 1.9459101 1.7851376 1.843978 0
## 442 1.0296194 0.9545494 2.541701 1
## 443 1.0296194 1.4105723 2.184184 1
## 444 2.3418058 1.9891065 1.877670 0
## 445 1.6486586 1.1289152 2.065342 0
## 446 1.3350011 1.6325097 1.526921 0
## 447 1.0296194 0.3747997 2.977611 1
## 448 2.0014800 1.8277056 1.713389 0
## 449 1.0296194 0.7285143 2.610510 1
## 450 1.0296194 0.9293649 2.267599 1
## 451 1.0296194 0.1605871 3.263885 1
## 452 0.6931472 1.3893646 2.400347 1
## 453 1.5260563 1.1311440 1.863380 0
## 454 1.0296194 0.4746180 3.014009 1
## 455 0.6931472 1.4815136 2.535494 1
## 456 1.3862944 1.6865286 1.932765 0
## 457 1.4816045 1.2774556 3.091618 0
## 458 2.0541237 1.7834752 2.675405 1
## 459 1.0296194 0.1218636 2.070798 1
## 460 1.7227666 1.2952476 2.215863 1
## 461 1.0296194 1.0221631 2.568253 1
## 462 1.0296194 0.7984977 2.475494 1
## 463 1.0296194 0.6604174 2.781511 1
## 464 1.0296194 0.7886392 2.291335 1
## 465 1.4586150 1.6122539 2.310850 0
## 466 1.0296194 0.5709795 2.950292 1
library(caret)
cm1 <- confusionMatrix(as.factor(df1$scored_target), as.factor(df1$target), positive="1", mode="everything") %>% print
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 221 17
## 1 16 212
##
## Accuracy : 0.9292
## 95% CI : (0.902, 0.9508)
## No Information Rate : 0.5086
## P-Value [Acc > NIR] : <2e-16
##
## Kappa : 0.8583
## Mcnemar's Test P-Value : 1
##
## Sensitivity : 0.9258
## Specificity : 0.9325
## Pos Pred Value : 0.9298
## Neg Pred Value : 0.9286
## Precision : 0.9298
## Recall : 0.9258
## F1 : 0.9278
## Prevalence : 0.4914
## Detection Rate : 0.4549
## Detection Prevalence : 0.4893
## Balanced Accuracy : 0.9291
##
## 'Positive' Class : 1
##
library(pROC)
curve1 <- roc(df1$target, df1$scored_target)
plot(curve1, main="pROC")

# Prediction for Test Data
crime_eval <- read.csv("https://raw.githubusercontent.com/xkong100/data-621/master/HW%203/crime-evaluation-data.csv", stringsAsFactors = FALSE, check.names = FALSE, na.strings = c("", "NA"))
head(crime_eval)
## zn indus chas nox rm age dis rad tax ptratio black lstat medv
## 1 0 7.07 0 0.469 7.185 61.1 4.9671 2 242 17.8 392.83 4.03 34.7
## 2 0 8.14 0 0.538 6.096 84.5 4.4619 4 307 21.0 380.02 10.26 18.2
## 3 0 8.14 0 0.538 6.495 94.4 4.4547 4 307 21.0 387.94 12.80 18.4
## 4 0 8.14 0 0.538 5.950 82.0 3.9900 4 307 21.0 232.60 27.71 13.2
## 5 0 5.96 0 0.499 5.850 41.5 3.9342 5 279 19.2 396.90 8.77 21.0
## 6 25 5.13 0 0.453 5.741 66.2 7.2254 8 284 19.7 395.11 13.15 18.7
summary(crime_eval)
## zn indus chas nox
## Min. : 0.000 Min. : 1.760 Min. :0.00 Min. :0.3850
## 1st Qu.: 0.000 1st Qu.: 5.692 1st Qu.:0.00 1st Qu.:0.4713
## Median : 0.000 Median : 8.915 Median :0.00 Median :0.5380
## Mean : 8.875 Mean :11.507 Mean :0.05 Mean :0.5592
## 3rd Qu.: 0.000 3rd Qu.:18.100 3rd Qu.:0.00 3rd Qu.:0.6258
## Max. :90.000 Max. :25.650 Max. :1.00 Max. :0.7400
## rm age dis rad
## Min. :3.561 Min. : 6.80 Min. :1.202 Min. : 1.000
## 1st Qu.:5.874 1st Qu.: 56.62 1st Qu.:2.041 1st Qu.: 4.000
## Median :6.143 Median : 83.25 Median :3.373 Median : 5.000
## Mean :6.214 Mean : 70.99 Mean :3.787 Mean : 9.775
## 3rd Qu.:6.532 3rd Qu.: 93.10 3rd Qu.:4.527 3rd Qu.:24.000
## Max. :8.247 Max. :100.00 Max. :9.089 Max. :24.000
## tax ptratio black lstat
## Min. :188.0 Min. :14.70 Min. : 50.92 Min. : 2.960
## 1st Qu.:276.8 1st Qu.:18.40 1st Qu.:367.56 1st Qu.: 6.435
## Median :307.0 Median :19.60 Median :391.64 Median :11.685
## Mean :393.5 Mean :19.12 Mean :351.48 Mean :12.905
## 3rd Qu.:666.0 3rd Qu.:20.20 3rd Qu.:395.29 3rd Qu.:17.363
## Max. :666.0 Max. :21.20 Max. :396.90 Max. :34.020
## medv
## Min. : 8.40
## 1st Qu.:16.98
## Median :20.55
## Mean :21.88
## 3rd Qu.:25.00
## Max. :50.00
attach(crime_eval)
## The following objects are masked from crime:
##
## age, black, chas, dis, indus, lstat, medv, nox, ptratio, rad,
## rm, tax, zn
T_sqrt_age1 <-sqrt(101-crime_eval$age)
T_log_ptratio1 <- log(22.2-crime_eval$ptratio)
T_log_dis1 <- log(crime_eval$dis)
T_cubic_lstat1 <- (crime_eval$lstat)^(1/3)
crime_eval<- crime_eval %>% mutate(sage=T_sqrt_age1,lptratio=T_log_ptratio1,ldis= T_log_dis1, clstat=T_cubic_lstat1) %>% dplyr ::select(-age,-ptratio,-dis,-lstat)
kable(head(crime_eval))
| 0 |
7.07 |
0 |
0.469 |
7.185 |
2 |
242 |
392.83 |
34.7 |
6.316645 |
1.4816045 |
1.602836 |
1.591360 |
| 0 |
8.14 |
0 |
0.538 |
6.096 |
4 |
307 |
380.02 |
18.2 |
4.062019 |
0.1823216 |
1.495575 |
2.172947 |
| 0 |
8.14 |
0 |
0.538 |
6.495 |
4 |
307 |
387.94 |
18.4 |
2.569046 |
0.1823216 |
1.493960 |
2.339214 |
| 0 |
8.14 |
0 |
0.538 |
5.950 |
4 |
307 |
232.60 |
13.2 |
4.358899 |
0.1823216 |
1.383791 |
3.026069 |
| 0 |
5.96 |
0 |
0.499 |
5.850 |
5 |
279 |
396.90 |
21.0 |
7.713624 |
1.0986123 |
1.369708 |
2.062212 |
| 25 |
5.13 |
0 |
0.453 |
5.741 |
8 |
284 |
395.11 |
18.7 |
5.899152 |
0.9162907 |
1.977603 |
2.360344 |
test_prediction <- predict(m3, newdata= crime_eval, type="response")
kable(head(bind_cols(crime_eval, data.frame(scored_target= test_prediction)) %>% mutate (scored_target= ifelse(scored_target > 0.5, 1, 0)) %>% print))
## zn indus chas nox rm rad tax black medv sage lptratio
## 1 0 7.07 0 0.469 7.185 2 242 392.83 34.7 6.316645 1.4816045
## 2 0 8.14 0 0.538 6.096 4 307 380.02 18.2 4.062019 0.1823216
## 3 0 8.14 0 0.538 6.495 4 307 387.94 18.4 2.569047 0.1823216
## 4 0 8.14 0 0.538 5.950 4 307 232.60 13.2 4.358899 0.1823216
## 5 0 5.96 0 0.499 5.850 5 279 396.90 21.0 7.713624 1.0986123
## 6 25 5.13 0 0.453 5.741 8 284 395.11 18.7 5.899152 0.9162907
## 7 25 5.13 0 0.453 5.966 8 284 378.08 16.0 2.756810 0.9162907
## 8 0 4.49 0 0.449 6.630 3 247 392.30 26.6 6.700746 1.3083328
## 9 0 4.49 0 0.449 6.121 3 247 395.15 22.2 6.648308 1.3083328
## 10 0 2.89 0 0.445 6.163 2 276 391.83 21.4 5.603570 1.4350845
## 11 0 25.65 0 0.581 5.856 2 188 370.31 17.3 2.000000 1.1314021
## 12 0 25.65 0 0.581 5.613 2 188 359.29 15.7 2.323790 1.1314021
## 13 0 21.89 0 0.624 5.637 4 437 396.90 14.3 2.509980 0.0000000
## 14 0 19.58 0 0.605 6.101 5 403 240.16 25.0 2.828427 2.0149030
## 15 0 19.58 0 0.605 5.880 5 403 348.13 19.1 1.923538 2.0149030
## 16 0 10.59 1 0.489 5.960 4 277 393.25 21.7 2.983287 1.2809338
## 17 0 6.20 0 0.504 6.552 8 307 380.34 31.5 8.921883 1.5686159
## 18 0 6.20 0 0.507 8.247 8 307 378.95 48.3 5.531727 1.5686159
## 19 22 5.86 0 0.431 6.957 7 330 386.09 29.6 9.705668 1.1314021
## 20 90 2.97 0 0.400 7.088 1 285 394.72 32.2 8.955445 1.9315214
## 21 80 1.76 0 0.385 6.230 1 241 341.60 20.1 8.336666 1.3862944
## 22 33 2.18 0 0.472 6.616 7 222 393.36 28.4 6.549809 1.3350011
## 23 0 9.90 0 0.544 6.122 4 304 396.90 22.1 6.942622 1.3350011
## 24 0 7.38 0 0.493 6.415 5 287 396.90 25.0 7.803845 0.9555114
## 25 0 7.38 0 0.493 6.312 5 287 396.90 23.0 8.491172 0.9555114
## 26 0 5.19 0 0.515 5.895 5 224 394.81 18.5 6.434283 0.6931472
## 27 80 2.01 0 0.435 6.635 4 280 390.94 24.5 8.443933 1.6486586
## 28 0 18.10 0 0.718 3.561 24 666 354.70 27.5 3.619392 0.6931472
## 29 0 18.10 1 0.631 7.016 24 666 392.05 50.0 1.870829 0.6931472
## 30 0 18.10 0 0.584 6.348 24 666 83.45 14.5 3.860052 0.6931472
## 31 0 18.10 0 0.740 5.935 24 666 68.95 8.4 3.619392 0.6931472
## 32 0 18.10 0 0.740 5.627 24 666 396.90 12.8 2.664583 0.6931472
## 33 0 18.10 0 0.740 5.818 24 666 391.45 10.5 2.932576 0.6931472
## 34 0 18.10 0 0.740 6.219 24 666 395.69 18.4 1.000000 0.6931472
## 35 0 18.10 0 0.740 5.854 24 666 240.52 10.8 2.097618 0.6931472
## 36 0 18.10 0 0.713 6.525 24 666 50.92 14.1 3.807887 0.6931472
## 37 0 18.10 0 0.713 6.376 24 666 391.43 17.7 3.549648 0.6931472
## 38 0 18.10 0 0.655 6.209 24 666 396.90 21.4 5.966574 0.6931472
## 39 0 9.69 0 0.585 5.794 6 391 396.90 18.3 5.513620 1.0986123
## 40 0 11.93 0 0.573 6.976 1 273 396.90 23.9 3.162278 0.1823216
## ldis clstat scored_target
## 1 1.6028362 1.591360 0
## 2 1.4955747 2.172947 1
## 3 1.4939597 2.339214 1
## 4 1.3837912 3.026069 1
## 5 1.3697076 2.062211 0
## 6 1.9776026 2.360344 0
## 7 1.9196395 2.435131 1
## 8 1.4901362 1.869122 0
## 9 1.3211156 2.036014 0
## 10 1.2513906 2.246662 0
## 11 0.6649534 2.939916 0
## 12 0.5637216 3.009599 0
## 13 0.6830463 2.637140 1
## 14 0.8256656 2.140703 1
## 15 0.8707493 2.291335 1
## 16 1.3550875 2.584823 0
## 17 1.2164250 1.554996 1
## 18 1.2952476 1.580759 1
## 19 2.1868038 1.522620 0
## 20 1.9888738 1.987421 0
## 21 2.2070869 2.347107 0
## 22 1.2149127 2.074677 0
## 23 0.9708925 1.815099 0
## 24 1.5520418 1.829155 0
## 25 1.6893391 1.832139 0
## 26 1.7254416 2.193923 1
## 27 2.1215427 1.816111 0
## 28 0.4782198 1.923800 1
## 29 0.1843196 1.435811 1
## 30 0.7191560 2.603152 1
## 31 0.5991661 3.240247 1
## 32 0.5972969 2.838912 1
## 33 0.6239043 2.806702 1
## 34 0.6955443 2.550442 1
## 35 0.6395354 2.876061 1
## 36 0.8902752 2.627035 1
## 37 0.9427769 2.446879 1
## 38 1.0863373 2.364525 1
## 39 1.0621903 2.415867 1
## 40 0.7735744 1.780026 0
| 0 |
7.07 |
0 |
0.469 |
7.185 |
2 |
242 |
392.83 |
34.7 |
6.316645 |
1.4816045 |
1.602836 |
1.591360 |
0 |
| 0 |
8.14 |
0 |
0.538 |
6.096 |
4 |
307 |
380.02 |
18.2 |
4.062019 |
0.1823216 |
1.495575 |
2.172947 |
1 |
| 0 |
8.14 |
0 |
0.538 |
6.495 |
4 |
307 |
387.94 |
18.4 |
2.569046 |
0.1823216 |
1.493960 |
2.339214 |
1 |
| 0 |
8.14 |
0 |
0.538 |
5.950 |
4 |
307 |
232.60 |
13.2 |
4.358899 |
0.1823216 |
1.383791 |
3.026069 |
1 |
| 0 |
5.96 |
0 |
0.499 |
5.850 |
5 |
279 |
396.90 |
21.0 |
7.713624 |
1.0986123 |
1.369708 |
2.062212 |
0 |
| 25 |
5.13 |
0 |
0.453 |
5.741 |
8 |
284 |
395.11 |
18.7 |
5.899152 |
0.9162907 |
1.977603 |
2.360344 |
0 |